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DBMS > Ignite vs. NSDb vs. Spark SQL vs. Splice Machine vs. StarRocks

System Properties Comparison Ignite vs. NSDb vs. Spark SQL vs. Splice Machine vs. StarRocks

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonStarRocks  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.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelKey-value store
Relational DBMS
Time Series DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score1.04
Rank#189  Overall
#88  Relational DBMS
Websiteignite.apache.orgnsdb.iospark.apache.org/­sqlsplicemachine.comwww.starrocks.io
Technical documentationapacheignite.readme.io/­docsnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperApache Software FoundationApache Software FoundationSplice MachineThe Linux Foundation infosince Feb 2023
Initial release20152017201420142020
Current releaseApache Ignite 2.63.5.0 ( 2.13), September 20233.1, March 20212.5.3, March 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetJava, ScalaScalaJavaC++, Java
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyesyesyes
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.yesnonono
Secondary indexesyesall fields are automatically indexednoyesyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like query languageSQL-like DML and DDL statementsyesyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
gRPC
HTTP REST
WebSocket
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
JDBC
MySQL protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Java
Scala
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nonoyes infoJavauser defined functions
Triggersyes (cache interceptors and events)noyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyesyes
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 implementationsnoAccess rights for users, groups and roles according to SQL-standardRole based access control and fine grained access rights

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More resources
IgniteNSDbSpark SQLSplice MachineStarRocks
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