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DBMS > Amazon SimpleDB vs. Datomic vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. Datomic vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDatomic  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#139  Overall
#24  Key-value stores
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.datomic.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.datomic.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAmazonCognitectSphinx Technologies Inc.Splice Machine
Initial release2007201220012014
Current release1.0.6735, June 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoGPL version 2, commercial licence availableOpen 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, ClojureC++Java
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesnoyes
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 indexesyes infoAll columns are indexed automaticallyyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Clojure
Java
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnoyes infoJava
TriggersnoBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationnone infoBut extensive use of caching in the application peersSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infoThe original contents of fields are not stored in the Sphinx index.yes
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 roles can be defined via the AWS Identity and Access Management (IAM)nonoAccess rights for users, groups and roles according to SQL-standard

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