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DBMS > BigObject vs. MarkLogic vs. Spark SQL vs. Sphinx vs. Teradata Aster

System Properties Comparison BigObject vs. MarkLogic vs. Spark SQL vs. Sphinx vs. Teradata Aster

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for real-time computations and queriesOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitebigobject.iowww.progress.com/­marklogicspark.apache.org/­sqlsphinxsearch.com
Technical documentationdocs.bigobject.iowww.progress.com/­marklogic/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperBigObject, Inc.MarkLogic Corp.Apache Software FoundationSphinx Technologies Inc.Teradata
Initial release20152001201420012005
Current release11.0, December 20223.5.0 ( 2.13), September 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree community edition availablecommercial inforestricted free version is availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial
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++ScalaC++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesschema-free infoSchema can be enforcedyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.noyesnoyes infoin Aster File Store
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL92SQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
Proprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresLuayes infovia XQuery or JavaScriptnonoR packages
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesnonenoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionnonoACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes, with Range Indexesnono
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsnonofine grained access rights according to SQL-standard

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More resources
BigObjectMarkLogicSpark SQLSphinxTeradata Aster
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