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DBMS > Amazon DocumentDB vs. Kinetica vs. OpenMLDB vs. Sadas Engine vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Kinetica vs. OpenMLDB vs. Sadas Engine vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonKinetica  Xexclude from comparisonOpenMLDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFully vectorized database across both GPUs and CPUsAn open-source machine learning database that provides a feature platform for training and inferenceSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.11
Rank#339  Overall
#30  Time Series DBMS
Score0.00
Rank#385  Overall
#159  Relational DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.kinetica.comopenmldb.aiwww.sadasengine.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.kinetica.comopenmldb.ai/­docs/­zh/­mainwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docs
DeveloperKinetica4 Paradigm Inc.SADAS s.r.l.Sphinx Technologies Inc.
Initial release20192012202020062001
Current release7.1, August 20212024-2 February 20248.03.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercial infofree trial version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++, Java, ScalaC++C++
Server operating systemshostedLinuxLinuxAIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesFixed schemayesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesyesSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
JDBC
SQLAlchemy
JDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functionsnonono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioninghorizontal partitioningSharding 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 replicasSource-replica replicationSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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 infoGPU vRAM or System RAMyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles on table levelfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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Amazon DocumentDBKineticaOpenMLDBSadas EngineSphinx
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