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DBMS > EXASOL vs. HBase vs. Microsoft Azure Synapse Analytics vs. RDF4J vs. Splice Machine

System Properties Comparison EXASOL vs. HBase vs. Microsoft Azure Synapse Analytics vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Wide-column store based on Apache Hadoop and on concepts of BigTableElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSWide column storeRelational DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.exasol.comhbase.apache.orgazure.microsoft.com/­services/­synapse-analyticsrdf4j.orgsplicemachine.com
Technical documentationwww.exasol.com/­resourceshbase.apache.org/­book.htmldocs.microsoft.com/­azure/­synapse-analyticsrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperExasolApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20002008201620042014
Current release2.3.4, January 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaJava
Server operating systemsLinux
Unix
Windows infousing Cygwin
hostedLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyesyes
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.nonono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesnoyesnoyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Java API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
Lua
Python
R
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
Java
PHP
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoCoprocessors in JavaTransact SQLyesyes infoJava
Triggersyesyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
EXASOLHBaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRDF4J infoformerly known as SesameSplice Machine
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