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DBMS > Amazon DocumentDB vs. GeoSpock vs. Ignite vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. GeoSpock vs. Ignite vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonIgnite  Xexclude from comparisonSplice Machine  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceSpatial and temporal data processing engine for extreme data scaleApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbgeospock.comignite.apache.orgsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesapacheignite.readme.io/­docssplicemachine.com/­how-it-works
DeveloperGeoSpockApache Software FoundationSplice Machine
Initial release201920152014
Current release2.0, September 2019Apache Ignite 2.63.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, JavascriptC++, Java, .NetJava
Server operating systemshostedhostedLinux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
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.nonoyes
Secondary indexesyestemporal, categoricalyesyes
SQL infoSupport of SQLnoANSI SQL for query only (using Presto)ANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)yes infoJava
Triggersnonoyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingShared 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 replicasyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes (compute grid and hadoop accelerator)Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACID
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.noyesyes
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per tableSecurity Hooks for custom implementationsAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBGeoSpockIgniteSplice Machine
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