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DBMS > Ignite vs. Interbase vs. Sadas Engine vs. Spark SQL vs. Splice Machine

System Properties Comparison Ignite vs. Interbase vs. Sadas Engine vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonInterbase  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  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.Light-weight proven RDBMS infooriginally from BorlandSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark 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 Spark
Primary database modelKey-value store
Relational DBMS
Relational 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
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteignite.apache.orgwww.embarcadero.com/­products/­interbasewww.sadasengine.comspark.apache.org/­sqlsplicemachine.com
Technical documentationapacheignite.readme.io/­docsdocs.embarcadero.com/­products/­interbasewww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationEmbarcaderoSADAS s.r.l.Apache Software FoundationSplice Machine
Initial release20151984200620142014
Current releaseApache Ignite 2.6InterBase 2020, December 20198.03.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree trial version availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
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, .NetCC++ScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
Android
iOS
Linux
OS X
Windows
AIX
Linux
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesno infoexport as XML data possiblenono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyesyesSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infoInterbase procedure and trigger languagenonoyes infoJava
Triggersyes (cache interceptors and events)yesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Interbase Change ViewsnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infomanaged by 'Learn by Usage'noyes
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
IgniteInterbaseSadas EngineSpark SQLSplice Machine
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