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DBMS > Amazon DocumentDB vs. Datomic vs. GigaSpaces vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Datomic vs. GigaSpaces vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatomic  Xexclude from comparisonGigaSpaces  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Search engine
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.datomic.comwww.gigaspaces.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datomic.comdocs.gigaspaces.com/­latest/­landing.htmlsphinxsearch.com/­docs
DeveloperCognitectGigaspaces TechnologiesSphinx Technologies Inc.
Initial release2019201220002001
Current release1.0.6735, June 202315.5, September 20203.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava, C++, .NetC++
Server operating systemshostedAll OS with a Java VMLinux
macOS
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nonono infoXML can be used for describing objects metadata
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-99 for query and DML statementsSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
Java
.Net
C++
Java
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyesno
TriggersnoBy using transaction functionsyes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnone infoBut extensive use of caching in the application peersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANY
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes
User concepts infoAccess controlAccess rights for users and rolesnoRole-based access controlno

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More resources
Amazon DocumentDBDatomicGigaSpacesSphinx
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