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DBMS > Amazon DocumentDB vs. Splice Machine vs. Trino

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

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonTrino  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 SparkFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.79
Rank#125  Overall
#23  Document stores
Score0.54
Rank#242  Overall
#114  Relational DBMS
Score5.18
Rank#60  Overall
#34  Relational DBMS
Websiteaws.amazon.com/­documentdbsplicemachine.comtrino.io
Technical documentationaws.amazon.com/­documentdb/­resourcessplicemachine.com/­how-it-workstrino.io/­broadcast
trino.io/­docs/­current
DeveloperSplice MachineTrino Software Foundation
Initial release201920142012 info2020 rebranded from PrestoSQL
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS infofor devlopment
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 indexesyesyesdepending on connected data-source
SQL infoSupport of SQLnoyesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native Spark Datasource
ODBC
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresnoyes infoJavayes, depending on connected data-source
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShared Nothhing Auto-Sharding, Columnar Partitioningdepending on connected data-source
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
depending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Yes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistencydepending on connected data-source
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesdepending on connected data-source
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-standardSQL standard access control
More information provided by the system vendor
Amazon DocumentDBSplice MachineTrino
News

73: Wrapping Trino packages with a bow
9 April 2025

Core Principles and Design Practices of OLAP Engines
27 March 2025

72: Keeping the lake clean
17 March 2025

Twenty four
3 March 2025

71: Fake it real good
27 February 2025

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Amazon DocumentDBSplice MachineTrino
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