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DBMS > Amazon DocumentDB vs. Splice Machine vs. TigerGraph

System Properties Comparison Amazon DocumentDB vs. Splice Machine vs. TigerGraph

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument storeRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score1.83
Rank#141  Overall
#13  Graph DBMS
Websiteaws.amazon.com/­documentdbsplicemachine.comwww.tigergraph.com
Technical documentationaws.amazon.com/­documentdb/­resourcessplicemachine.com/­how-it-worksdocs.tigergraph.com
DeveloperSplice Machine
Initial release201920142017
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GSQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native Spark Datasource
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoyes infoJavayes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShared 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 replicasMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Yes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standardRole-based access control

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More resources
Amazon DocumentDBSplice MachineTigerGraph
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