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DBMS > Databricks vs. GigaSpaces vs. Microsoft Azure AI Search vs. TimesTen

System Properties Comparison Databricks vs. GigaSpaces vs. Microsoft Azure AI Search vs. TimesTen

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure AI Search  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSearch-as-a-service for web and mobile app developmentAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelDocument store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Search engineRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitewww.databricks.comwww.gigaspaces.comazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmllearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperDatabricksGigaspaces TechnologiesMicrosoftOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2013200020151998
Current release15.5, September 2020V1Release 22.1
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net
Server operating systemshostedLinux
macOS
Solaris
Windows
hostedIBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesno infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL-99 for query and DML statementsnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP APIODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesPython
R
Scala
.Net
C++
Java
Python
Scala
C#
Java
JavaScript
Python
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnoPL/SQL
Triggersyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyesnoyes
User concepts infoAccess controlRole-based access controlyes infousing Azure authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGigaSpacesMicrosoft Azure AI SearchTimesTen
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGigaSpacesMicrosoft Azure AI SearchTimesTen
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