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DBMS > ObjectBox vs. Sphinx vs. Splice Machine vs. Teradata Aster vs. ToroDB

System Properties Comparison ObjectBox vs. Sphinx vs. Splice Machine vs. Teradata Aster vs. ToroDB

Editorial information provided by DB-Engines
NameObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonToroDB  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionExtremely fast embedded database for small devices, IoT and MobileOpen 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 typesA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelObject oriented DBMSSearch engineRelational DBMSRelational DBMSDocument store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.22
Rank#172  Overall
#5  Object oriented DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteobjectbox.iosphinxsearch.comsplicemachine.comgithub.com/­torodb/­server
Technical documentationdocs.objectbox.iosphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperObjectBox LimitedSphinx Technologies Inc.Splice MachineTeradata8Kdata
Initial release20172001201420052016
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C++JavaJava
Server operating systemsAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
LinuxAll OS with a Java 7 VM
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 dateyesnoyesyesyes infostring, integer, double, boolean, date, object_id
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 indexesyesyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)yesyes
APIs and other access methodsProprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
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#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyes infoJavaR packages
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar PartitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesonline/offline synchronization between client and servernoneMulti-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.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDno
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 controlyesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles
More information provided by the system vendor
ObjectBoxSphinxSplice MachineTeradata AsterToroDB
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More resources
ObjectBoxSphinxSplice MachineTeradata AsterToroDB
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