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DBMS > Elasticsearch vs. Ingres vs. Spark SQL vs. Splice Machine vs. Trafodion

System Properties Comparison Elasticsearch vs. Ingres vs. Spark SQL vs. Splice Machine vs. Trafodion

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonIngres  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricWell established RDBMSSpark 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 SparkTransactional SQL-on-Hadoop DBMS
Primary database modelSearch engineRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score132.83
Rank#7  Overall
#1  Search engines
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.elastic.co/­elasticsearchwww.actian.com/­databases/­ingresspark.apache.org/­sqlsplicemachine.comtrafodion.apache.org
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmldocs.actian.com/­ingresspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-workstrafodion.apache.org/­documentation.html
DeveloperElasticActian CorporationApache Software FoundationSplice MachineApache Software Foundation, originally developed by HP
Initial release20101974 infooriginally developed at University Berkely in early 1970s201420142014
Current release8.6, January 202311.2, May 20223.5.0 ( 2.13), September 20233.1, March 20212.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
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 languageJavaCScalaJavaC++, Java
Server operating systemsAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyesyes
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.nono infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyes infoAll search fields are automatically indexedyesnoyesyes
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statementsyesyes
APIs and other access methodsJava API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesyesnoyes infoJavaJava Stored Procedures
Triggersyes infoby using the 'percolation' featureyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesIngres ReplicatornoneMulti-source replication
Source-replica replication
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop ConnectornoYes, via Full Spark Integrationyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes, multi-version concurrency control (MVCC)yes
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.Memcached and Redis integrationnonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
ElasticsearchIngresSpark SQLSplice MachineTrafodion
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