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DBMS > Apache Ignite vs. Databricks vs. EDB Postgres

System Properties Comparison Apache Ignite vs. Databricks vs. EDB Postgres

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Editorial information provided by DB-Engines
NameApache Ignite  Xexclude from comparisonDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.
Primary database modelKey-value store
Relational DBMS
Document store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.89
Rank#87  Overall
#13  Key-value stores
#47  Relational DBMS
Score90.03
Rank#13  Overall
#2  Document stores
#9  Relational DBMS
Score1.64
Rank#134  Overall
#62  Relational DBMS
Websiteignite.apache.orgwww.databricks.comwww.enterprisedb.com
Technical documentationapacheignite.readme.io/­docsdocs.databricks.comwww.enterprisedb.com/­docs
DeveloperApache Software FoundationDatabricksEnterpriseDB
Initial release201520132005
Current release2.16.0, December 202314, December 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infoBSD for PostgreSQL-components
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC
Server operating systemsLinux
OS X
Solaris
Windows
hostedLinux
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLwith Databricks SQLyes infostandard with numerous extensions
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Python
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)user defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or range
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache IgniteDatabricksEDB Postgres
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache IgniteDatabricksEDB Postgres
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GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2025
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Real-time in-memory OLTP and Analytics with Apache Ignite on AWS
14 May 2016, AWS Blog

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

GridGain, Apache Ignite founder talks in-memory databases
11 August 2022, TechTarget

GridGain In-Memory Data Fabric Becomes Apache Ignite
9 April 2015, Linux.com

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