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DBMS > Amazon DocumentDB vs. GigaSpaces vs. ObjectBox vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. ObjectBox vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonObjectBox  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsExtremely fast embedded database for small devices, IoT and MobileOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Object oriented DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbwww.gigaspaces.comobjectbox.iosplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.gigaspaces.com/­latest/­landing.htmldocs.objectbox.iosplicemachine.com/­how-it-works
DeveloperGigaspaces TechnologiesObjectBox LimitedSplice Machine
Initial release2019200020172014
Current release15.5, September 20203.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache License 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 languageJava, C++, .NetC and C++Java
Server operating systemshostedLinux
macOS
Solaris
Windows
Android
iOS
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsnoyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Proprietary native APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C++
Java
Python
Scala
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyes infoJava
Triggersnoyes, event driven architecturenoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnoneShared 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 infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
online/offline synchronization between client and serverMulti-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 infoMap-Reduce pattern can be built with XAP task executorsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesyes
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlyesAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon DocumentDBGigaSpacesObjectBoxSplice Machine
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More resources
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