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DBMS > FoundationDB vs. LevelDB vs. Postgres-XL vs. Spark SQL vs. TigerGraph

System Properties Comparison FoundationDB vs. LevelDB vs. Postgres-XL vs. Spark SQL vs. TigerGraph

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonLevelDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeRelational DBMSRelational DBMSGraph DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitegithub.com/­apple/­foundationdbgithub.com/­google/­leveldbwww.postgres-xl.orgspark.apache.org/­sqlwww.tigergraph.com
Technical documentationapple.github.io/­foundationdbgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperFoundationDBGoogleApache Software Foundation
Initial release201320112014 infosince 2012, originally named StormDB20142017
Current release6.2.28, November 20201.23, February 202110 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSDOpen Source infoMozilla public licenseOpen Source infoApache 2.0commercial
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 languageC++C++CScalaC++
Server operating systemsLinux
OS X
Windows
Illumos
Linux
OS X
Windows
Linux
macOS
Linux
OS X
Windows
Linux
Data schemeschema-free infosome layers support schemasschema-freeyesyesyes
Typing infopredefined data types such as float or dateno infosome layers support typingnoyesyesyes
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 infoXML type, but no XML query functionalitynono
Secondary indexesnonoyesno
SQL infoSupport of SQLsupported in specific SQL layer onlynoyes infodistributed, parallel query executionSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresin SQL-layer onlynouser defined functionsnoyes
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoMVCCnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardnoRole-based access control

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More resources
FoundationDBLevelDBPostgres-XLSpark SQLTigerGraph
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