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DBMS > Amazon DocumentDB vs. Blazegraph vs. FoundationDB vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Blazegraph vs. FoundationDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonFoundationDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Ordered key-value store. Core features are complimented by layers.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeGraph DBMS
RDF store
Document store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­documentdbblazegraph.comgithub.com/­apple/­foundationdbsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourceswiki.blazegraph.comapple.github.io/­foundationdbsplicemachine.com/­how-it-works
DeveloperBlazegraphFoundationDBSplice Machine
Initial release2019200620132014
Current release2.1.5, March 20196.2.28, November 20203.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoextended commercial license availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-free infosome layers support schemasyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesno infosome layers support typingyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnoSPARQL is used as query languagesupported in specific SQL layer onlyyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesin SQL-layer onlyyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationLinearizable consistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in Graphsin SQL-layer onlyyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and rolesSecurity and Authentication via Web Application Container (Tomcat, Jetty)noAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBBlazegraphFoundationDBSplice Machine
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