DBMS > Ignite vs. PostgreSQL vs. Prometheus
System Properties Comparison Ignite vs. PostgreSQL vs. Prometheus
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|Editorial information provided by DB-Engines|
|Name||Ignite Xexclude from comparison||PostgreSQL Xexclude from comparison||Prometheus Xexclude from comparison|
|Description||Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.||Widely used open source RDBMS Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL||Open-source TimeSeries DBMS and monitoring system|
|Primary database model||Key-value store|
|Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.||Time Series DBMS|
|Secondary database models||Document store|
Graph DBMS with Apache Age
Vector DBMS with pgvector extension
|Developer||Apache Software Foundation||PostgreSQL Global Development Group www.postgresql.org/developer|
|Initial release||2015||1989 1989: Postgres, 1996: PostgreSQL||2015|
|Current release||Apache Ignite 2.6||16.0, September 2023|
|License Commercial or Open Source||Open Source Apache 2.0||Open Source BSD||Open Source Apache 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.|
|Implementation language||C++, Java, .Net||C||Go|
|Server operating systems||Linux|
|Typing predefined data types such as float or date||yes||yes||Numeric data only|
|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 specific XML-type available, but no XML query functionality.||no Import of XML data possible|
|SQL Support of SQL||ANSI-99 for query and DML statements, subset of DDL||yes standard with numerous extensions||no|
|APIs and other access methods||HDFS API|
RESTful HTTP API
native C library
streaming API for large objects
|RESTful HTTP/JSON API|
|Supported programming languages||C#|
|Server-side scripts Stored procedures||yes (compute grid and cache interceptors can be used instead)||user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.||no|
|Triggers||yes (cache interceptors and events)||yes||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||partitioning by range, list and (since PostgreSQL 11) by hash||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||yes (replicated cache)||Source-replica replication other methods possible by using 3rd party extensions||yes by Federation|
|MapReduce Offers an API for user-defined Map/Reduce methods||yes (compute grid and hadoop accelerator)||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency||none|
|Foreign keys Referential integrity||no||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||yes||no||no|
|User concepts Access control||Security Hooks for custom implementations||fine grained access rights according to SQL-standard||no|
More information provided by the system vendor
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|Related products and services|
|3rd parties||Datasentinel: Platform for Monitoring and Analyzing the performance problems of your PostgreSQL Clusters|
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|DB-Engines blog posts|
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|Conferences and events|
PostgreSQL 101: An introduction to Multi-Version Concurrency Control and Vacuum
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