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DBMS > GigaSpaces vs. Rockset vs. Sphinx vs. Splice Machine vs. Teradata

System Properties Comparison GigaSpaces vs. Rockset vs. Sphinx vs. Splice Machine vs. Teradata

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonRockset  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA scalable, reliable search and analytics service in the cloud, built on RocksDBOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Document storeSearch engineRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Relational DBMS
Search engine
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.gigaspaces.comrockset.comsphinxsearch.comsplicemachine.comwww.teradata.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.rockset.comsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperGigaspaces TechnologiesRocksetSphinx Technologies Inc.Splice MachineTeradata
Initial release20002019200120141984
Current release15.5, September 20203.5.1, February 20233.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++C++Java
Server operating systemsLinux
macOS
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
hosted
Linux
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesdynamic typingnoyesyes
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.no infoXML can be used for describing objects metadatano infoingestion from XML files supportedyes
Secondary indexesyesall fields are automatically indexedyes infofull-text index on all search fieldsyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-99 for query and DML statementsRead-only SQL queries, including JOINsSQL-like query language (SphinxQL)yesyes infoSQL 2016 + extensions
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP RESTProprietary protocolJDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C++
Java
Python
Scala
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesnonoyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersyes, event driven architecturenonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlRole-based access controlAccess rights for users and organizations can be defined via Rockset consolenoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GigaSpacesRocksetSphinxSplice MachineTeradata
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