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XML Databases
XML databases are a type of database that stores, manages, and retrieves data in the XML (Extensible Markup Language) format. These databases are designed to handle semi-structured data, where data is stored in a tree-like structure using tags, making it more flexible than traditional relational databases. XML databases support querying and manipulating XML data using specialized languages such as XPath, XQuery, and XML Schema. They are commonly used in applications that require complex data structures, such as content management systems, document storage, and web services. XML databases allow for efficient handling of large and dynamic datasets while maintaining the hierarchical relationships between elements, making them suitable for applications that need to store and retrieve structured or semi-structured data efficiently.
Database Software
Database software and database management systems are a type of software designed to store, manage and retrieve data. It is used to organize all kinds of information in an efficient manner, allowing users to quickly access the data they need. Many databases are tailored for specific purposes and applications, ranging from transaction processing systems to large-scale analytics platforms. Database software may be used on its own or connected with other software services for complex operations.
Key-Value Databases
Key-value databases are a type of NoSQL database that store data as pairs, where each unique key is associated with a value. This structure is simple and highly flexible, making key-value databases ideal for scenarios requiring fast access to data, such as caching, session management, and real-time applications. In these databases, the key acts as a unique identifier for retrieving or storing the value, which can be any type of data—strings, numbers, objects, or even binary data. Key-value stores are known for their scalability, performance, and ability to handle high volumes of read and write operations with low latency. These databases are particularly useful for applications that require quick lookups or high availability, such as online retail platforms, social networks, and recommendation systems.
Graph Databases
Graph databases are specialized databases designed to store, manage, and query data that is represented as graphs. Unlike traditional relational databases that use tables to store data, graph databases use nodes, edges, and properties to represent and store data. Nodes represent entities (such as people, products, or locations), edges represent relationships between entities, and properties store information about nodes and edges. Graph databases are particularly well-suited for applications that involve complex relationships and interconnected data, such as social networks, recommendation engines, fraud detection, and network analysis.
Database Security Software
Database security software helps organizations protect databases and sensitive data from unauthorized access, cyber threats, insider risks, and compliance violations. These platforms provide capabilities such as activity monitoring, access controls, vulnerability assessment, encryption, auditing, threat detection, and policy enforcement across on-premises, cloud, and hybrid database environments. The software often includes real-time monitoring, privileged user oversight, anomaly detection, database firewall functionality, data masking, and compliance reporting to help safeguard critical information assets. Many database security solutions integrate with identity and access management (IAM), SIEM, data loss prevention (DLP), vulnerability management, and security operations platforms to provide comprehensive database protection. By continuously monitoring database activity and enforcing security policies, database security software helps organizations reduce data breach risks, maintain regulatory compliance, and protect sensitive business information.
Columnar Databases
Columnar databases, also known as column-oriented databases or column-store databases, are a type of database that store data in columns instead of rows. Columnar databases have some advantages over traditional row databases including speed and efficiency.
Database Monitoring Tools
Database monitoring tools help businesses and IT teams track, analyze, and optimize the performance of their databases to ensure smooth operation, prevent downtime, and maintain data integrity. These tools typically provide features for real-time monitoring of database metrics such as query performance, response times, CPU and memory usage, and disk space utilization. Database monitoring software often includes alerting mechanisms for detecting issues such as slow queries or resource bottlenecks, as well as detailed reporting and analytics to improve database efficiency and scalability. By using these tools, organizations can proactively manage database health, troubleshoot problems, and optimize system performance.
Relational Database
Relational database software provides users with the tools to capture, store, search, retrieve and manage information in data points related to one another.
Database Backup Software
Database backup software solutions enable organizations to back up their databases so that they can restore the databases if necessary. Database backup software is essential for companies of all kinds that want to protect against corrupted data, broken hardware, or employee missteps.
Time Series Databases
Time series databases (TSDB) are databases designed to store time series and time-stamped data as pairs of times and values. Time series databases are useful for easily managing and analyzing time series.
NoSQL Database
NoSQL database software provides the tools to store, capture and retrieve of big data through the use of non tabular databases.
Distributed Databases
Distributed databases store data across multiple physical locations, often across different servers or even geographical regions, allowing for high availability and scalability. Unlike traditional databases, distributed databases divide data and workloads among nodes in a network, providing faster access and load balancing. They are designed to be resilient, with redundancy and data replication ensuring that data remains accessible even if some nodes fail. Distributed databases are essential for applications that require quick access to large volumes of data across multiple locations, such as global eCommerce, finance, and social media. By decentralizing data storage, they support high-performance, fault-tolerant operations that scale with an organization’s needs.
Database Virtualization Software
Database virtualization software provides IT professionals a solution for virtualization databases in order to allow the pooling and usage of resources to be allocated when needed.
Database Design Software
Database design software is a type of computer program used to create, modify and manage databases. It enables users to define the structure of a database and the relationships between different data fields. It also allows the user to perform various operations on existing databases such as editing, backing up, transferring data and creating reports.
Vector Databases
Vector databases are a type of database that use vector-based data structures, rather than the traditional relational models, to store information. They are used in artificial intelligence (AI) applications such as machine learning, natural language processing and image recognition. Vector databases support fast and efficient data storage and retrieval processes, making them an ideal choice for AI use cases. They also enable the integration of structured and unstructured datasets into a single system, offering enhanced scalability for complex projects.
Document Databases
Document databases are a type of NoSQL database designed to store, manage, and retrieve semi-structured data in the form of documents, typically using formats like JSON, BSON, or XML. Unlike traditional relational databases, document databases do not require a fixed schema, allowing for greater flexibility in handling diverse and evolving data structures. Each document in the database can contain different fields and data types, making it ideal for applications where data is complex and varied. These databases excel at scaling horizontally, making them well-suited for handling large volumes of data across distributed systems. Document databases are commonly used in modern web and mobile applications, where they provide efficient storage and fast access to rich, nested data structures.
OLAP Databases
OLAP (Online Analytical Processing) databases are designed to support complex queries and data analysis, typically for business intelligence and decision-making purposes. They enable users to interactively explore large volumes of multidimensional data, offering fast retrieval of insights across various dimensions such as time, geography, and product categories. OLAP databases use specialized structures like cubes to allow for rapid aggregation and calculation of data. These databases are highly optimized for read-heavy operations, making them ideal for generating reports, dashboards, and analytical queries. Overall, OLAP databases help organizations quickly analyze data to uncover patterns, trends, and insights for better decision-making.
SQL Databases
SQL databases are structured systems that use the Structured Query Language (SQL) to store, retrieve, and manage data. They organize data into tables with rows and columns, ensuring that information is easily accessible, consistent, and scalable. SQL databases are widely used in applications that require complex queries, transactions, and data integrity, making them essential for web applications, financial systems, and enterprise environments. These databases offer robust features for security, data normalization, and maintaining relationships between different datasets. Overall, SQL databases are fundamental to managing relational data efficiently and reliably across various industries.
Embedded Database Systems
Embedded database systems are lightweight, self-contained databases that are integrated directly into applications, allowing data management without requiring a separate database server. They are optimized for performance and simplicity, often running within the same process as the host application, making them ideal for use in mobile apps, IoT devices, and small-scale applications. These databases support SQL or other query languages and offer full database functionality, including transaction management and data integrity. Embedded database systems are designed to operate with minimal configuration, providing fast, reliable data storage and retrieval within constrained environments. Their ease of integration and low resource usage make them essential for applications that need efficient local data management without the overhead of external databases.
Database Clients
Database clients are tools or applications used to connect to a database server and interact with its data. They allow users to perform operations such as querying, updating, inserting, and deleting records through a structured language. These clients often offer intuitive interfaces or command-line options to simplify database management tasks. They are essential for managing data efficiently, catering to both small-scale and enterprise-level needs. By providing a bridge between users and the database, they streamline data access and administration.
View more categories (20) for "delphi database"

34 Products for "delphi database" with 2 filters applied:

  • 1
    Google Cloud BigQuery
    BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more...
    Starting Price: Free ($300 in free credits)
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  • 2
    Databricks

    Databricks

    Databricks

    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with...
  • 3
    Teradata VantageCloud
    Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It...
  • 4
    Snowflake

    Snowflake

    Snowflake

    Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates...
    Starting Price: $2/credit
  • 5
    AllegroGraph

    AllegroGraph

    Franz Inc.

    AllegroGraph is a breakthrough solution that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph utilizes unique federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph provides users with an integrated version of Gruff, a unique browser-based graph...
  • 6
    Metal

    Metal

    Metal

    ...Learn how to use our Typescript SDK to implement Metal into your application. Although we love TypeScript, you can of course utilize this library in JavaScript. Mechanism to fine-tune your spp programmatically. Indexed vector database of your embeddings. Resources that represent your specific ML use-case.
    Starting Price: $25 per month
  • 7
    Robin.io

    Robin.io

    Robin.io

    ...Our approach extends Kubernetes for data-intensive applications such as Hortonworks, Cloudera, Elastic stack, RDBMS, NoSQL databases, and AI/ML apps. Facilitates simpler and faster roll-out of critical Enterprise IT and LoB initiatives, such as containerization, cloud-migration, cost-consolidation, and productivity improvement. Solves the fundamental challenges of running big data and databases in Kubernetes.
  • 8
    Oracle Machine Learning
    ...Increase data scientist and developer productivity and reduce their learning curve with familiar open source-based Apache Zeppelin notebook technology. Notebooks support SQL, PL/SQL, Python, and markdown interpreters for Oracle Autonomous Database so users can work with their language of choice when developing models. A no-code user interface supporting AutoML on Autonomous Database to improve both data scientist productivity and non-expert user access to powerful in-database algorithms for classification and regression. Data scientists gain integrated model deployment from the Oracle Machine Learning AutoML User Interface.
  • 9
    Edge Intelligence

    Edge Intelligence

    Edge Intelligence

    ...It's the fastest, easiest way to analyze vast amounts of geographically distributed data. A new approach to analytics. Overcome the architectural constraints associated with traditional big data warehouses, database design and edge computing architectures. Understand details within the platform that allow for centralized command & control, automated software installation & orchestration and geographically distributed data input & storage.
  • 10
    Qualdo

    Qualdo

    Qualdo

    We are a leader in Data Quality & ML Model for enterprises adopting a multi-cloud, ML and modern data management ecosystem. Algorithms to track Data Anomalies in Azure, GCP & AWS databases. Measure and monitor data issues from all your cloud database management tools and data silos, using a single, centralized tool. Quality is in the eye of the beholder. Data issues have different implications depending on where you sit in the enterprise. Qualdo is a pioneer in organizing all data quality management issues through the lens of multiple enterprise stakeholders, presenting a unified view in a consumable format. ...
  • 11
    ClearScape Analytics
    ​ClearScape Analytics is Teradata's advanced analytics engine, offering powerful, open, and connected AI/ML capabilities designed to deliver better answers and faster results. It provides robust in-database analytics, enabling users to solve complex problems with extensive in-database analytic functions. It supports various languages and APIs, achieving frictionless connectivity with best-in-class open source and partner AI/ML tools. With the "Bring Your Own Analytics" feature, organizations can operationalize all their models, even those developed in other tools. ...
  • 12
    Rapidminer AI Studio
    ...It allows data scientists and engineers to build, train, and test AI models locally, giving organizations full control and flexibility for initial exploration and development. It connects directly to enterprise data sources, including files, databases, data lakes, cloud data platforms, warehouses, SQL databases, and Internet of Things data streams, helping teams unify data, prevent errors, and power accurate, explainable AI. RapidMiner AI Studio supports both domain experts and technical teams: users without coding experience can quickly build effective machine learning models with an intuitive drag-and-drop canvas, while data scientists can create complex models in a fully integrated notebook environment using Python and R.
  • 13
    Eternity AI

    Eternity AI

    Eternity AI

    ...For a model to think like a human, it needs to get access to real-time knowledge and everything about how humans behave. Members of our team have previously published white papers and articles on topics related to on-chain vulnerability coordination, GPT database retrieval, decentralized dispute resolution, etc.
  • 14
    Metis Augmented Predictive Intelligence
    ...The Metis Augmented Predictive Intelligence Platform automates the collection, analysis and resolution of meaningful data points that reveal the full extent of past incidents and help accurately predict future risks. Metis can take it all – video, audio, correspondence, social media posts, satellite images, and other databases – and make sense of it to thoroughly expose criminal activity and identify emerging threats.
  • 15
    Pachyderm

    Pachyderm

    Pachyderm

    Pachyderm’s Data Versioning gives teams an automated and performant way to keep track of all data changes. File-based versioning provides a complete audit trail for all data and artifacts across pipeline stages, including intermediate results. Stored as native objects (not metadata pointers) so that versioning is automated and guaranteed. Autoscale with parallel processing of data without writing additional code. Incremental processing saves compute by only processing differences and...
  • 16
    Tecton

    Tecton

    Tecton

    ...Serve features in production at extreme scale with the confidence that systems will always be up and running. Tecton meets strict security and compliance standards. Tecton is not a database or a processing engine. It plugs into and orchestrates on top of your existing storage and processing infrastructure.
  • 17
    Nitromia

    Nitromia

    Nitromia

    Unlocking the power of fully homomorphic encryption for financial institutions. Imagine a world where you can extract insights from your data and perform advanced analytics without worrying about data leakage, attacks and compliance. With Nitromia’s fully homomorphic cryptography, companies perform advanced data science and computations at minimum risk with zero exposure for data at rest and in transit. The Platform. Based on cutting edge fully homomorphic technology, Nitromia’s enablement...
  • 18
    PI.EXCHANGE

    PI.EXCHANGE

    PI.EXCHANGE

    Easily connect your data to the engine, either through uploading a file or connecting to a database. Then, start analyzing your data through visualizations, or prepare your data for machine learning modeling with the data wrangling actions with repeatable recipes. Get the most out of your data by building machine learning models, using regression, classification or clustering algorithms - all without any code. Uncover insights into your data, using the feature importance, prediction explanation, and what-if tools. ...
    Starting Price: $39 per month
  • 19
    Yandex DataSphere

    Yandex DataSphere

    Yandex.Cloud

    ...Everything will be created automatically with no need to manage infrastructure. Choose an operating mode: serverless or dedicated. Manage project data, save it to datasets, and set up connections to databases, object storage, or other repositories, all in one interface. Collaborate with colleagues around the world to create an ML model, share the project, and set budgets for teams across your organization. Launch your ML in minutes, without the help of developers. Run experiments with simultaneous publication of different versions of models.
    Starting Price: $0.095437 per GB
  • 20
    SquareML

    SquareML

    SquareML

    ...It enables users, regardless of technical expertise, to harness machine learning capabilities without extensive coding knowledge. The platform specializes in data ingestion from multiple sources, including electronic health records, claims databases, medical devices, and health information exchanges. Key features include a no-code data science lifecycle, generative AI models for healthcare, unstructured data conversion, diverse machine learning models for predicting patient outcomes and disease progression, a library of pre-built models and algorithms, and seamless integration with various healthcare data sources. ...
  • 21
    Amazon Lookout for Metrics
    Reduce false positives and use machine learning (ML) to accurately detect anomalies in business metrics. Diagnose the root cause of anomalies by grouping related outliers together. Summarize root causes and rank them by severity. Seamlessly integrate AWS databases, storage services, and third-party SaaS applications to monitor metrics and detect anomalies. Automate customized alerts and actions when anomalies are detected. Automatically detect anomalies within metrics and identify their root causes. Lookout for Metrics uses ML to detect and diagnose anomalies within business and operational data. ...
  • 22
    evoML

    evoML

    TurinTech AI

    ...It automates crucial steps, automatic data transformation that detects anomalies and handles imbalances, feature engineering via genetic algorithms, parallel model evaluation across thousands of candidates, multi-objective optimization on custom metrics, and GenAI-based synthetic data generation for rapid prototyping under data-privacy constraints. Users fully own and customize generated model code for seamless deployment as APIs, databases, or local libraries, avoiding vendor lock-in and ensuring transparent, auditable workflows. EvoML empowers teams with intuitive visualizations, interactive dashboards, and charts to identify patterns, outliers, and anomalies for use cases such as anomaly detection, time-series forecasting, and fraud prevention.
  • 23
    Activeloop

    Activeloop

    Activeloop

    Activeloop provides a continuous learning infrastructure for teams building software, agents, and data pipelines. Its core product, Deeplake, is the GPU database for agents, built around the idea that if your AI is on a GPU, your data should be too. Deeplake is designed to keep AI agents grounded, versioned, queryable, and GPU-native by combining vector and tensor data in one store, with GPU streaming to fine-tuning and a serverless Postgres interface. It gives teams a data engine for multimodal AI, allowing them to store, index, search, and stream data to models and agents. ...
  • 24
    Predibase

    Predibase

    Predibase

    ...Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple. Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want.
  • 25
    DataRobot

    DataRobot

    DataRobot

    ...The AI Catalog enables seamlessly finding, sharing, tagging, and reusing data, helping to speed time to production and increase collaboration. The catalog provides easy access to the data needed to answer a business problem while ensuring security, compliance, and consistency. If your database is protected by a network policy that only allows connections from specific IP addresses, contact Support for a list of addresses that an administrator must add to your network policy (whitelist).
  • 26
    XLSCOUT

    XLSCOUT

    XLSCOUT

    ...XLSCOUT engineered data with best-in-class artificial intelligence technologies to develop the most accurate, comprehensive, and intelligent patent & research publication database. Using Natural Language Processing (NLP), Machine Learning (ML), and innovation/scientific principles, XLSCOUT gives you more time and reliable insights to confidently make data-driven strategic decisions. Drafting LLM is a cutting-edge patent application drafting platform that utilizes Large Language Models (LLMs) & Generative AI for drafting top-tier preliminary patent drafts. ...
  • 27
    Cinchapi

    Cinchapi

    Cinchapi

    ...Cinchapi does all the number crunching and highlights the most important insights, so you focus on the signal instead of being distracted by the noise. Cinchapi uses a combination of machine learning and advanced heuristics to enrich your data with additional context. Cinchapi's version-control database allows you to pause or rewind real-time data and explore every possible dimension in depth.
  • 28
    OpenCV

    OpenCV

    OpenCV

    ...These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, and stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery, etc.
    Starting Price: Free
  • 29
    Rapidminer SLC
    ...Rapidminer SLC allows users to create, execute, and operationalize analytics across on-premises, cloud, and hybrid environments. It supports access to many data sources, including cloud services, Hadoop, data warehouses, databases, Excel, CSV, SPSS, SAS language data, and other file formats. With Rapidminer Analytics Workbench and SLC Hub, organizations can improve governance, scheduling, security, deployment, and workload management across the full analytics lifecycle.
  • 30
    Volcano Engine

    Volcano Engine

    Volcano Engine

    Volcengine is ByteDance’s cloud platform delivering a full spectrum of IaaS, PaaS, and AI services under its Volcano Ark ecosystem through global, multi‑region infrastructure. It provides elastic compute instances (CPU, GPU, and TPU), high‑performance block and object storage, virtual networking, and managed databases, all designed for seamless scalability and pay‑as‑you‑go flexibility. Integrated AI capabilities offer natural language processing, computer vision, and speech recognition via prebuilt models or custom training pipelines, while a content delivery network and Engine VE SDK enable adaptive‑bitrate streaming, low‑latency media delivery, and real‑time AR/VR rendering. ...
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