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DBMS > FoundationDB vs. NSDb vs. Splice Machine

System Properties Comparison FoundationDB vs. NSDb vs. Splice Machine

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonNSDb  Xexclude from comparisonSplice Machine  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­apple/­foundationdbnsdb.iosplicemachine.com
Technical documentationapple.github.io/­foundationdbnsdb.io/­Architecturesplicemachine.com/­how-it-works
DeveloperFoundationDBSplice Machine
Initial release201320172014
Current release6.2.28, November 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ScalaJava
Server operating systemsLinux
OS X
Windows
Linux
macOS
Linux
OS X
Solaris
Windows
Data schemeschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateno infosome layers support typingyes: int, bigint, decimal, stringyes
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.no
Secondary indexesnoall fields are automatically indexedyes
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query languageyes
APIs and other access methodsgRPC
HTTP REST
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
Java
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresin SQL-layer onlynoyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standard

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More resources
FoundationDBNSDbSplice Machine
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