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DBMS > Kinetica vs. LMDB vs. Microsoft Azure Cosmos DB vs. Sphinx

System Properties Comparison Kinetica vs. LMDB vs. Microsoft Azure Cosmos DB vs. Sphinx

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLMDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsA high performant, light-weight, embedded key-value database libraryGlobally distributed, horizontally scalable, multi-model database serviceOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Search engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.kinetica.comwww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­services/­cosmos-dbsphinxsearch.com
Technical documentationdocs.kinetica.comwww.lmdb.tech/­doclearn.microsoft.com/­azure/­cosmos-dbsphinxsearch.com/­docs
DeveloperKineticaSymasMicrosoftSphinx Technologies Inc.
Initial release2012201120142001
Current release7.1, August 20210.9.32, January 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CC++
Server operating systemsLinuxLinux
Unix
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoJSON typesno
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
Secondary indexesyesnoyes infoAll properties auto-indexed by defaultyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Proprietary protocol
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsnoJavaScriptno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDMulti-item ACID transactions with snapshot isolation within a partitionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 RAMyes
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights can be defined down to the item levelno

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More resources
KineticaLMDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSphinx
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