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DBMS > Apache Impala vs. Graph Engine vs. Postgres-XL vs. Splice Machine

System Properties Comparison Apache Impala vs. Graph Engine vs. Postgres-XL vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSGraph DBMS
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteimpala.apache.orgwww.graphengine.iowww.postgres-xl.orgsplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.graphengine.io/­docs/­manualwww.postgres-xl.org/­documentationsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftSplice Machine
Initial release201320102014 infosince 2012, originally named StormDB2014
Current release4.1.0, June 202210 R1, October 20183.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoMozilla public licenseOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++.NET and CCJava
Server operating systemsLinux.NETLinux
macOS
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infodistributed, parallel query executionyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
F#
Visual Basic
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functionsyes infoJava
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioninghorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache ImpalaGraph Engine infoformer name: TrinityPostgres-XLSplice Machine
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