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DBMS > Databricks vs. Kinetica vs. Manticore Search vs. Microsoft Azure Table Storage

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fully vectorized database across both GPUs and CPUsMulti-storage database for search, including full-text search.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engineWide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitewww.databricks.comwww.kinetica.commanticoresearch.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.databricks.comdocs.kinetica.commanual.manticoresearch.com
DeveloperDatabricksKineticaManticore SoftwareMicrosoft
Initial release2013201220172012
Current release7.1, August 20216.0, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++
Server operating systemshostedLinuxFreeBSD
Linux
macOS
Windows
hosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schemaschema-free
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.yesnoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
RESTful HTTP API
Supported programming languagesPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenono
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 service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationSynchronous replication based on Galera libraryyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes infoisolated transactions for atomic changes and binary logging for safe writesoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and roles on table levelnoAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
DatabricksKineticaManticore SearchMicrosoft Azure Table Storage
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksKineticaManticore SearchMicrosoft Azure Table Storage
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