DBMS > GridGain vs. IBM Db2 vs. Oracle Berkeley DB vs. PostgreSQL vs. Vertica
System Properties Comparison GridGain vs. IBM Db2 vs. Oracle Berkeley DB vs. PostgreSQL vs. Vertica
Editorial information provided by DB-Engines | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Name | GridGain Xexclude from comparison | IBM Db2 formerly named DB2 or IBM Database 2 Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | PostgreSQL Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | GridGain is an in-memory computing platform, built on Apache Ignite | Common in IBM host environments, 2 different versions for host and Windows/Linux | Widely used in-process key-value store | Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Key-value store Relational DBMS | Relational DBMS Since Version 10.5 support for JSON/BSON documents compatible with MongoDB | Key-value store supports sorted and unsorted key sets Native XML DBMS in the Oracle Berkeley DB XML version | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store RDF store in Db2 LUW (Linux, Unix, Windows) Spatial DBMS with Db2 Spatial Extender | Document store Graph DBMS with Apache Age Spatial DBMS Vector DBMS with pgvector extension | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Website | www.gridgain.com | www.ibm.com/products/db2 | www.oracle.com/database/technologies/related/berkeleydb.html | www.postgresql.org | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | www.gridgain.com/docs/index.html | www.ibm.com/docs/en/db2 | docs.oracle.com/cd/E17076_05/html/index.html | www.postgresql.org/docs | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | GridGain Systems, Inc. | IBM | Oracle originally developed by Sleepycat, which was acquired by Oracle | PostgreSQL Global Development Group www.postgresql.org/developer | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2007 | 1983 host version | 1994 | 1989 1989: Postgres, 1996: PostgreSQL | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | GridGain 8.5.1 | 12.1, October 2016 | 18.1.40, May 2020 | 16.3, May 2024 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | commercial free version is available | Open Source commercial license available | Open Source BSD | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. |
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java, C++, .Net | C and C++ | C, Java, C++ (depending on the Berkeley DB edition) | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Solaris Windows | AIX HP-UX Linux Solaris Windows z/OS | AIX Android FreeBSD iOS Linux OS X Solaris VxWorks Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | yes | schema-free | yes | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT. | yes | yes only with the Berkeley DB XML edition | yes specific XML-type available, but no XML query functionality. | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | yes | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | ANSI-99 for query and DML statements, subset of DDL | yes | yes SQL interfaced based on SQLite is available | yes standard with numerous extensions | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | HDFS API Hibernate JCache JDBC ODBC Proprietary protocol RESTful HTTP API Spring Data | ADO.NET JDBC JSON style queries MongoDB compatible ODBC XQuery | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Java PHP Python Ruby Scala | C C# C++ Cobol Delphi Fortran Java Perl PHP Python Ruby Visual Basic | .Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET others Third-party libraries to manipulate Berkeley DB files are available for many languages C C# C++ Java JavaScript (Node.js) 3rd party binding Perl Python Tcl | .Net C C++ Delphi Java JDBC JavaScript (Node.js) Perl PHP Python Tcl | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes (compute grid and cache interceptors can be used instead) | yes | no | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes (cache interceptors and events) | yes | yes only for the SQL API | yes | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding only with Windows/Unix/Linux Version | none | partitioning by range, list and (since PostgreSQL 11) by hash | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | yes (replicated cache) | yes with separate tools (MQ, InfoSphere) | Source-replica replication | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes (compute grid and hadoop accelerator) | no | no | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | ACID | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Security Hooks for custom implementations | fine grained access rights according to SQL-standard | no | fine grained access rights according to SQL-standard | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GridGain | IBM Db2 formerly named DB2 or IBM Database 2 | Oracle Berkeley DB | PostgreSQL | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of system vendors to contact us for updating and extending the system information, | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Related products and services | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3rd parties | Timescale: Calling all PostgreSQL users – the 2023 State of PostgreSQL survey is now open! Share your favorite extensions, preferred frameworks, community experiences, and more. Take the survey today!
» more CYBERTEC is your professional partner in PostgreSQL topics for over 20 years. As our main aim is to be your single-source all-in-one IT service provider, we offer a wide range of products and services. Visit our website for more details. » more SharePlex is the reliable and affordable data replication solution for PostgreSQL migrations, high availability and more. » more Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems. » more Redgate webinars: A series of key topics for new PostgreSQL users. » more Fujitsu Enterprise Postgres: An Enterprise Grade PostgreSQL with the flexibility of a hybrid cloud solution combined with industry leading security, availability and performance. » more Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. » more pgDash: In-Depth PostgreSQL Monitoring. » more Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools. » more Instaclustr: Fully Hosted & Managed PostgreSQL » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
We invite representatives of vendors of related products to contact us for presenting information about their offerings here. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GridGain | IBM Db2 formerly named DB2 or IBM Database 2 | Oracle Berkeley DB | PostgreSQL | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | GridGain in-memory data and generative AI – Blocks and Files GridGain's 2023 Growth Positions Company for Strong 2024 GridGain Unified Real-Time Data Platform Version 8.9 Addresses Today's More Complex Real-Time Data Processing ... GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024 GridGain: Product Overview and Analysis provided by Google News | Use AWS DMS to migrate data from IBM Db2 DPF to an AWS target | Amazon Web Services IBM Collaborates with AWS to Launch a New Cloud Database Offering, Enabling Customers to Optimize Data ... IBM's vintage Db2 database jumps on AWS's cloud bandwagon Precisely Supports Amazon RDS for Db2 Service with Real-Time Data Integration Capabilities Blog Theme - Details provided by Google News | Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions ACM recognizes far-reaching technical achievements with special awards Margo I. Seltzer | Berkman Klein Center Oracle buys Sleepycat Software Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag provided by Google News | A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions Timescale unveils high-performance AI vector database extensions for PostgreSQL PostgreSQL Tutorial: Definition, Commands, & Features How To Schedule PostgreSQL Backups With GitHub Actions provided by Google News | HP Rolls Out Vertica Marketplace for Big Data Analytics MapR Hadoop Upgrade Runs HP Vertica Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations Postgres pioneer Michael Stonebraker promises to upend the database once more provided by Google News |
Share this page