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DBMS > Kinetica vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

System Properties Comparison Kinetica vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsMulti-storage database for search, including full-text search.Globally distributed, horizontally scalable, multi-model database serviceA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Wide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
Time Series DBMS infousing the Manticore Columnar LibrarySpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score0.26
Rank#312  Overall
#21  Search engines
Score30.39
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score5.35
Rank#71  Overall
#6  Wide column stores
Websitewww.kinetica.commanticoresearch.comazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.kinetica.commanual.manticoresearch.comlearn.microsoft.com/­azure/­cosmos-db
DeveloperKineticaManticore SoftwareMicrosoftMicrosoft
Initial release2012201720142012
Current release7.1, August 20216.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++
Server operating systemsLinuxFreeBSD
Linux
macOS
Windows
hostedhosted
Data schemeyesFixed schemaschema-freeschema-free
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infoJSON typesyes
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.noCan index from XMLno
Secondary indexesyesyes infofull-text index on all search fieldsyes infoAll properties auto-indexed by defaultno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
RESTful HTTP API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsJavaScriptno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoJavaScriptno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud serviceyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
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 configurationBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infoisolated transactions for atomic changes and binary logging for safe writesMulti-item ACID transactions with snapshot isolation within a partitionoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights can be defined down to the item levelAccess rights based on private key authentication or shared access signatures

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More resources
KineticaManticore SearchMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Table Storage
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