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DBMS > LevelDB vs. PostgreSQL vs. Splice Machine vs. TimesTen

System Properties Comparison LevelDB vs. PostgreSQL vs. Splice Machine vs. TimesTen

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Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkIn-Memory RDBMS compatible to Oracle
Primary database modelKey-value storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#115  Overall
#19  Key-value stores
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitegithub.com/­google/­leveldbwww.postgresql.orgsplicemachine.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.postgresql.org/­docssplicemachine.com/­how-it-worksdocs.oracle.com/­database/­timesten-18.1
DeveloperGooglePostgreSQL Global Development Group infowww.postgresql.org/­developerSplice MachineOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20111989 info1989: Postgres, 1996: PostgreSQL20141998
Current release1.23, February 202116.3, May 20243.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoBSDOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJava
Server operating systemsIllumos
Linux
OS X
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyes infostandard with numerous extensionsyesyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoJavaPL/SQL
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and (since PostgreSQL 11) by hashShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyes 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.noyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
LevelDBPostgreSQLSplice MachineTimesTen
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