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DBMS > Databricks vs. GridGain vs. Microsoft Azure AI Search vs. Sphinx vs. Teradata Aster

System Properties Comparison Databricks vs. GridGain vs. Microsoft Azure AI Search vs. Sphinx vs. Teradata Aster

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.GridGain is an in-memory computing platform, built on Apache IgniteSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Search engineSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.databricks.comwww.gridgain.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmllearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperDatabricksGridGain Systems, Inc.MicrosoftSphinx Technologies Inc.Teradata
Initial release20132007201520012005
Current releaseGridGain 8.5.1V13.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availablecommercial
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 languageJava, C++, .NetC++
Server operating systemshostedLinux
OS X
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesyesnoyes infoin Aster File Store
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP APIProprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)nonoR packages
Triggersyes (cache interceptors and events)nonono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)yes infoImplicit feature of the cloud servicenoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsyes infousing Azure authenticationnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGridGainMicrosoft Azure AI SearchSphinxTeradata Aster
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGridGainMicrosoft Azure AI SearchSphinxTeradata Aster
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