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DBMS > Databricks vs. Infobright vs. Sphinx

System Properties Comparison Databricks vs. Infobright vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonInfobright  Xexclude from comparisonSphinx  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 performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score1.00
Rank#193  Overall
#90  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.databricks.comignitetech.com/­softwarelibrary/­infobrightdbsphinxsearch.com
Technical documentationdocs.databricks.comsphinxsearch.com/­docs
DeveloperDatabricksIgnite Technologies Inc.; formerly InfoBright Inc.Sphinx Technologies Inc.
Initial release201320052001
Current release3.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemshostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesno
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 indexesyesno infoKnowledge Grid Technology used insteadyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLyesSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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.noyes
User concepts infoAccess controlfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesno
More information provided by the system vendor
DatabricksInfobrightSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksInfobrightSphinx
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