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DBMS > Greenplum vs. LeanXcale vs. Splice Machine vs. Teradata Aster vs. TimesTen

System Properties Comparison Greenplum vs. LeanXcale vs. Splice Machine vs. Teradata Aster vs. TimesTen

Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonLeanXcale  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTimesTen  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesOpen-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 typesIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitegreenplum.orgwww.leanxcale.comsplicemachine.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.greenplum.orgsplicemachine.com/­how-it-worksdocs.oracle.com/­database/­timesten-18.1
DeveloperPivotal Software Inc.LeanXcaleSplice MachineTeradataOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20052015201420051998
Current release7.0.0, September 20233.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoAGPL 3.0, commercial license availablecommercialcommercial
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 languageJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
LinuxAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
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.yes infosince Version 4.2yes infoin Aster File Storeno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyes infothrough Apache Derbyyesyesyes
APIs and other access methodsJDBC
ODBC
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
Java
Perl
Python
R
C
Java
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresyesyes infoJavaR packagesPL/SQL
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-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.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integrationyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GreenplumLeanXcaleSplice MachineTeradata AsterTimesTen
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