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DBMS > Databricks vs. Hypertable vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Databricks vs. Hypertable vs. Microsoft Azure AI Search vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is 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.An open source BigTable implementation based on distributed file systems such as HadoopSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Wide column storeSearch engineSearch engine
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
Score5.52
Rank#59  Overall
#6  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperDatabricksHypertable Inc.MicrosoftSphinx Technologies Inc.
Initial release2013200920152001
Current release0.9.8.11, March 2016V13.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoGPL version 2, commercial licence available
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 languageC++C++
Server operating systemshostedLinux
OS X
Windows infoan inofficial Windows port is available
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or datenoyesno
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
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
C++ API
Thrift
RESTful HTTP APIProprietary protocol
Supported programming languagesPython
R
Scala
C++
Java
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonono
Triggersnonono
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 supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor on file system levelyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes infousing Azure authenticationno
More information provided by the system vendor
DatabricksHypertableMicrosoft Azure AI SearchSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHypertableMicrosoft Azure AI SearchSphinx
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