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DBMS > Ignite vs. RethinkDB vs. Splice Machine vs. Teradata Aster

System Properties Comparison Ignite vs. RethinkDB vs. Splice Machine vs. Teradata Aster

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Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonRethinkDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.DBMS for the Web with a mechanism to push updated query results to applications in realtime.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value store
Relational DBMS
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score2.84
Rank#106  Overall
#19  Document stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteignite.apache.orgrethinkdb.comsplicemachine.com
Technical documentationapacheignite.readme.io/­docsrethinkdb.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software FoundationThe Linux Foundation infosince July 2017Splice MachineTeradata
Initial release2015200920142005
Current releaseApache Ignite 2.62.4.1, August 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC++Java
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes infostring, binary, float, bool, date, geometryyesyes
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.yesnoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoyesyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infoJavaR packages
Triggersyes (cache interceptors and events)Client-side triggers through changefeedsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding inforange basedShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replicationMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yesYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-document operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCC basedyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsyes infousers and table-level permissionsAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
IgniteRethinkDBSplice MachineTeradata Aster
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