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DBMS > GeoSpock vs. Sphinx vs. Splice Machine vs. Teradata Aster vs. Yanza

System Properties Comparison GeoSpock vs. Sphinx vs. Splice Machine vs. Teradata Aster vs. Yanza

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonYanza  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleOpen 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 SparkPlatform for big data analytics on multistructured data sources and typesTime Series DBMS for IoT Applications
Primary database modelRelational DBMSSearch engineRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegeospock.comsphinxsearch.comsplicemachine.comyanza.com
Technical documentationsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperGeoSpockSphinx Technologies Inc.Splice MachineTeradataYanza
Initial release2001201420052015
Current release2.0, September 20193.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, JavascriptC++Java
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
LinuxWindows
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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.noyes infoin Aster File Storeno
Secondary indexestemporal, categoricalyes infofull-text index on all search fieldsyesyesno
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like query language (SphinxQL)yesyesno
APIs and other access methodsJDBCProprietary protocolJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
HTTP API
Supported programming languagesC++ 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#
C++
Java
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyes infoJavaR packagesno
Triggersnonoyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-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.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users can be defined per tablenoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
GeoSpockSphinxSplice MachineTeradata AsterYanza
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