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DBMS > Databricks vs. Kinetica vs. Microsoft Azure AI Search vs. NSDb vs. TimesTen

System Properties Comparison Databricks vs. Kinetica vs. Microsoft Azure AI Search vs. NSDb vs. TimesTen

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonNSDb  Xexclude from comparisonTimesTen  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 CPUsSearch-as-a-service for web and mobile app developmentScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engineTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector DBMS
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
Score5.59
Rank#63  Overall
#7  Search engines
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websitewww.databricks.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­searchnsdb.iowww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databricks.comdocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­searchnsdb.io/­Architecturedocs.oracle.com/­database/­timesten-18.1
DeveloperDatabricksKineticaMicrosoftOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20132012201520171998
Current release7.1, August 2021V111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++Java, Scala
Server operating systemshostedLinuxhostedLinux
macOS
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes
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.yesnononono
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLSQL-like DML and DDL statementsnoSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIgRPC
HTTP REST
WebSocket
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
Java
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnonoPL/SQL
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 infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelyes infousing Azure authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksKineticaMicrosoft Azure AI SearchNSDbTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksKineticaMicrosoft Azure AI SearchNSDbTimesTen
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