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DBMS > Amazon DocumentDB vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonSplice Machine  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 Spark
Primary database modelDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#126  Overall
#24  Document stores
Score0.54
Rank#243  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcessplicemachine.com/­how-it-works
DeveloperSplice Machine
Initial release20192014
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesyes
SQL infoSupport of SQLnoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyes
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 Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes
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 rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBSplice Machine
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