Difference between ActivePivot and AnzoGraph Last Updated : 15 Jul, 2025 Comments Improve Suggest changes Like Article Like Report 1. ActivePivot : The ActivePivot is an in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data. This database uses a columnar storage architecture along with dictionary compression and binary representation of Java objects. It is one of the core products of the French company ActiveViam – once known as Quartet FS, which was founded in 2005. 2. AnzoGraph : It is an in-memory distributed graph DBMS designed for analytics. It is used in embedded analytics. This DB is a massively parallel processing (MPP) native graph database built for diverse data harmonization and analytics at scale, speed and deep link insights. Difference between ActivePivot and AnzoGraph : S.NO. ActivePivot AnzoGraph 1. It was developed by ActiveViam. It was developed by Cambridge Semantics in 2018. 2. It is an in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data. It is an in-memory distributed graph DBMS designed for analytics. 3. The license of ActivePivot is commercial. The license of AnzoGraph is also commercial. 4. It is not available as a cloud service. It is also not available as a cloud service. 5. Its primary database model is Object-Oriented DBMS. Its primary database model are Graph DBMS and RDF Store. 6. It supports the Server-side scripting with Post-processors in Java. It supports the user defined functions for Server-side scripting. 7. It supports in-memory capabilities. It also supports in-memory capabilities. 8. It supports SQL query language with Multi-Dimensional Expressions (MDX). It supports SPARQL is used as query language. Comment More infoAdvertise with us Next Article Introduction of DBMS (Database Management System) S shubhamsingh10 Follow Improve Article Tags : DBMS Difference Between Similar Reads DBMS Tutorial – Learn Database Management System Database Management System (DBMS) is a software used to manage data from a database. A database is a structured collection of data that is stored in an electronic device. The data can be text, video, image or any other format.A relational database stores data in the form of tables and a NoSQL databa 7 min read Basic of DBMSIntroduction of DBMS (Database Management System)A Database Management System (DBMS) is a software solution designed to efficiently manage organize and retrieve data in a structured manner. It allows users to create, modify and query databases while ensuring data integrity, security and efficient data access. Unlike traditional file systems, DBMS 6 min read History of DBMSThe first database management systems (DBMS) were created to handle complex data for businesses in the 1960s. These systems included Charles Bachman's Integrated Data Store (IDS) and IBM's Information Management System (IMS). Databases were first organized into tree-like structures using hierarchica 7 min read DBMS Architecture 1-level, 2-Level, 3-LevelA DBMS architecture defines how users interact with the database to read, write, or update information. A well-designed architecture and schema (a blueprint detailing tables, fields and relationships) ensure data consistency, improve performance and keep data secure.Types of DBMS Architecture There 6 min read Difference between File System and DBMSA file system and a DBMS are two kinds of data management systems that are used in different capacities and possess different characteristics. A File System is a way of organizing files into groups and folders and then storing them in a storage device. It provides the media that stores data as well 6 min read Entity Relationship ModelIntroduction of ER ModelThe Entity-Relationship Model (ER Model) is a conceptual model for designing a databases. This model represents the logical structure of a database, including entities, their attributes and relationships between them. Entity: An objects that is stored as data such as Student, Course or Company.Attri 10 min read Structural Constraints of Relationships in ER ModelStructural constraints, within the context of Entity-Relationship (ER) modeling, specify and determine how the entities take part in the relationships and this gives an outline of how the interactions between the entities can be designed in a database. Two primary types of constraints are cardinalit 5 min read Generalization, Specialization and Aggregation in ER ModelUsing the ER model for bigger data creates a lot of complexity while designing a database model, So in order to minimize the complexity Generalization, Specialization and Aggregation were introduced in the ER model. These were used for data abstraction. In which an abstraction mechanism is used to h 4 min read Introduction of Relational Model and Codd Rules in DBMSThe Relational Model is a fundamental concept in Database Management Systems (DBMS) that organizes data into tables, also known as relations. This model simplifies data storage, retrieval, and management by using rows and columns. Codd’s Rules, introduced by Dr. Edgar F. Codd, define the principles 14 min read Keys in Relational ModelIn the context of a relational database, keys are one of the basic requirements of a relational database model. Keys are fundamental components that ensure data integrity, uniqueness and efficient access. It is widely used to identify the tuples(rows) uniquely in the table. We also use keys to set u 6 min read Mapping from ER Model to Relational ModelConverting an Entity-Relationship (ER) diagram to a Relational Model is a crucial step in database design. The ER model represents the conceptual structure of a database, while the Relational Model is a physical representation that can be directly implemented using a Relational Database Management S 7 min read Strategies for Schema design in DBMSThere are various strategies that are considered while designing a schema. Most of these strategies follow an incremental approach that is, they must start with some schema constructs derived from the requirements and then they incrementally modify, refine or build on them. What is Schema Design?Sch 6 min read Relational ModelIntroduction of Relational Algebra in DBMSRelational Algebra is a formal language used to query and manipulate relational databases, consisting of a set of operations like selection, projection, union, and join. It provides a mathematical framework for querying databases, ensuring efficient data retrieval and manipulation. Relational algebr 9 min read SQL Joins (Inner, Left, Right and Full Join)SQL joins are fundamental tools for combining data from multiple tables in relational databases. For example, consider two tables where one table (say Student) has student information with id as a key and other table (say Marks) has information about marks of every student id. Now to display the mar 4 min read Join operation Vs Nested query in DBMSThe concept of joins and nested queries emerged to facilitate the retrieval and management of data stored in multiple, often interrelated tables within a relational database. As databases are normalized to reduce redundancy, the meaningful information extracted often requires combining data from dif 3 min read Tuple Relational Calculus (TRC) in DBMSTuple Relational Calculus (TRC) is a non-procedural query language used to retrieve data from relational databases by describing the properties of the required data (not how to fetch it). It is based on first-order predicate logic and uses tuple variables to represent rows of tables.Syntax: The basi 4 min read Domain Relational Calculus in DBMSDomain Relational Calculus (DRC) is a formal query language for relational databases. It describes queries by specifying a set of conditions or formulas that the data must satisfy. These conditions are written using domain variables and predicates, and it returns a relation that satisfies the specif 4 min read Relational AlgebraIntroduction of Relational Algebra in DBMSRelational Algebra is a formal language used to query and manipulate relational databases, consisting of a set of operations like selection, projection, union, and join. It provides a mathematical framework for querying databases, ensuring efficient data retrieval and manipulation. Relational algebr 9 min read SQL Joins (Inner, Left, Right and Full Join)SQL joins are fundamental tools for combining data from multiple tables in relational databases. For example, consider two tables where one table (say Student) has student information with id as a key and other table (say Marks) has information about marks of every student id. Now to display the mar 4 min read Join operation Vs Nested query in DBMSThe concept of joins and nested queries emerged to facilitate the retrieval and management of data stored in multiple, often interrelated tables within a relational database. As databases are normalized to reduce redundancy, the meaningful information extracted often requires combining data from dif 3 min read Tuple Relational Calculus (TRC) in DBMSTuple Relational Calculus (TRC) is a non-procedural query language used to retrieve data from relational databases by describing the properties of the required data (not how to fetch it). It is based on first-order predicate logic and uses tuple variables to represent rows of tables.Syntax: The basi 4 min read Domain Relational Calculus in DBMSDomain Relational Calculus (DRC) is a formal query language for relational databases. It describes queries by specifying a set of conditions or formulas that the data must satisfy. These conditions are written using domain variables and predicates, and it returns a relation that satisfies the specif 4 min read Functional Dependencies & NormalizationAttribute Closure in DBMSFunctional dependency and attribute closure are essential for maintaining data integrity and building effective, organized and normalized databases. Attribute closure of an attribute set can be defined as set of attributes which can be functionally determined from it.How to find attribute closure of 4 min read Armstrong's Axioms in Functional Dependency in DBMSArmstrong's Axioms refer to a set of inference rules, introduced by William W. Armstrong, that are used to test the logical implication of functional dependencies. Given a set of functional dependencies F, the closure of F (denoted as F+) is the set of all functional dependencies logically implied b 4 min read Canonical Cover of Functional Dependencies in DBMSManaging a large set of functional dependencies can result in unnecessary computational overhead. This is where the canonical cover becomes useful. A canonical cover is a set of functional dependencies that is equivalent to a given set of functional dependencies but is minimal in terms of the number 7 min read Normal Forms in DBMSIn the world of database management, Normal Forms are important for ensuring that data is structured logically, reducing redundancy, and maintaining data integrity. When working with databases, especially relational databases, it is critical to follow normalization techniques that help to eliminate 7 min read The Problem of Redundancy in DatabaseRedundancy means having multiple copies of the same data in the database. This problem arises when a database is not normalized. Suppose a table of student details attributes is: student ID, student name, college name, college rank, and course opted. Student_ID Name Contact College Course Rank 100Hi 6 min read Lossless Join and Dependency Preserving DecompositionDecomposition of a relation is done when a relation in a relational model is not in appropriate normal form. Relation R is decomposed into two or more relations if decomposition is lossless join as well as dependency preserving. Lossless Join DecompositionIf we decompose a relation R into relations 4 min read Denormalization in DatabasesDenormalization is a database optimization technique in which we add redundant data to one or more tables. This can help us avoid costly joins in a relational database. Note that denormalization does not mean 'reversing normalization' or 'not to normalize'. It is an optimization technique that is ap 4 min read Transactions & Concurrency ControlACID Properties in DBMSIn the world of DBMS, transactions are fundamental operations that allow us to modify and retrieve data. However, to ensure the integrity of a database, it is important that these transactions are executed in a way that maintains consistency, correctness, and reliability. This is where the ACID prop 6 min read Types of Schedules in DBMSScheduling is the process of determining the order in which transactions are executed. When multiple transactions run concurrently, scheduling ensures that operations are executed in a way that prevents conflicts or overlaps between them.There are several types of schedules, all of them are depicted 6 min read Recoverability in DBMSRecoverability ensures that after a failure, the database can restore a consistent state by keeping committed changes and undoing uncommitted ones. It uses logs to redo or undo actions, preventing data loss and maintaining integrity.There are several levels of recoverability that can be supported by 5 min read Implementation of Locking in DBMSLocking protocols are used in database management systems as a means of concurrency control. Multiple transactions may request a lock on a data item simultaneously. Hence, we require a mechanism to manage the locking requests made by transactions. Such a mechanism is called a Lock Manager. It relies 5 min read Deadlock in DBMSA deadlock occurs in a multi-user database environment when two or more transactions block each other indefinitely by each holding a resource the other needs. This results in a cycle of dependencies (circular wait) where no transaction can proceed.For Example: Consider the image belowDeadlock in DBM 4 min read Starvation in DBMSStarvation in DBMS is a problem that happens when some processes are unable to get the resources they need because other processes keep getting priority. This can happen in situations like locking or scheduling, where some processes keep getting the resources first, leaving others waiting indefinite 8 min read Advanced DBMSIndexing in DatabasesIndexing in DBMS is used to speed up data retrieval by minimizing disk scans. Instead of searching through all rows, the DBMS uses index structures to quickly locate data using key values.When an index is created, it stores sorted key values and pointers to actual data rows. This reduces the number 6 min read Introduction of B TreeA B-Tree is a specialized m-way tree designed to optimize data access, especially on disk-based storage systems. In a B-Tree of order m, each node can have up to m children and m-1 keys, allowing it to efficiently manage large datasets.The value of m is decided based on disk block and key sizes.One 8 min read Introduction of B+ TreeA B+ Tree is an advanced data structure used in database systems and file systems to maintain sorted data for fast retrieval, especially from disk. It is an extended version of the B Tree, where all actual data is stored only in the leaf nodes, while internal nodes contain only keys for navigation.C 5 min read Bitmap Indexing in DBMSBitmap Indexing is a powerful data indexing technique used in Database Management Systems (DBMS) to speed up queries- especially those involving large datasets and columns with only a few unique values (called low-cardinality columns).In a database table, some columns only contain a few different va 3 min read Inverted IndexAn Inverted Index is a data structure used in information retrieval systems to efficiently retrieve documents or web pages containing a specific term or set of terms. In an inverted index, the index is organized by terms (words), and each term points to a list of documents or web pages that contain 7 min read SQL Queries on Clustered and Non-Clustered IndexesIndexes in SQL play a pivotal role in enhancing database performance by enabling efficient data retrieval without scanning the entire table. The two primary types of indexes Clustered Index and Non-Clustered Index serve distinct purposes in optimizing query performance. In this article, we will expl 7 min read File Organization in DBMSFile organization in DBMS refers to the method of storing data records in a file so they can be accessed efficiently. It determines how data is arranged, stored, and retrieved from physical storage.The Objective of File OrganizationIt helps in the faster selection of records i.e. it makes the proces 5 min read DBMS PracticeLast Minute Notes - DBMSDatabase Management System is an organized collection of interrelated data that helps in accessing data quickly, along with efficient insertion, and deletion of data into the DBMS. DBMS organizes data in the form of tables, schemas, records, etc. DBMS over File System (Limitations of File System)The 15+ min read Top 60 DBMS Interview Questions with Answers for 2025A Database Management System (DBMS) is the backbone of modern data storage and management. Understanding DBMS concepts is critical for anyone looking to work with databases. Whether you're preparing for your first job in database management or advancing in your career, being well-prepared for a DBMS 15+ min read Commonly asked DBMS Interview Questions | Set 2This article is an extension of Commonly asked DBMS interview questions | Set 1.Q1. There is a table where only one row is fully repeated. Write a Query to find the Repeated rowNameSectionabcCS1bcdCS2abcCS1In the above table, we can find duplicate rows using the below query.SELECT name, section FROM 5 min read Like