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DBMS > FoundationDB vs. Hazelcast vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Spark SQL

System Properties Comparison FoundationDB vs. Hazelcast vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Spark SQL

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.A widely adopted in-memory data gridDatabase as a Service offering with high compatibility to Microsoft SQL ServerBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Graph DBMS
Spatial DBMS
Document 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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegithub.com/­apple/­foundationdbhazelcast.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.postgres-xl.orgspark.apache.org/­sql
Technical documentationapple.github.io/­foundationdbhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBHazelcastMicrosoftApache Software Foundation
Initial release2013200820102014 infosince 2012, originally named StormDB2014
Current release6.2.28, November 20205.3.6, November 2023V1210 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++CScala
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedLinux
macOS
Linux
OS X
Windows
Data schemeschema-free infosome layers support schemasschema-freeyesyesyes
Typing infopredefined data types such as float or dateno infosome layers support typingyesyesyesyes
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 infothe object must implement a serialization strategyyesyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query languageyesyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlyyes infoEvent Listeners, Executor ServicesTransact SQLuser defined functionsno
Triggersnoyes infoEventsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoRole-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
FoundationDBHazelcastMicrosoft Azure SQL Database infoformerly SQL AzurePostgres-XLSpark SQL
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