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DBMS > Databricks vs. Sphinx vs. Sqrrl vs. Tkrzw

System Properties Comparison Databricks vs. Sphinx vs. Sqrrl vs. Tkrzw

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonSphinx  Xexclude from comparisonSqrrl  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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.Open source search engine for searching in data from different sources, e.g. relational databasesAdaptable, secure NoSQL built on Apache AccumuloA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Relational DBMS
Search engineDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.databricks.comsphinxsearch.comsqrrl.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comsphinxsearch.com/­docs
DeveloperDatabricksSphinx Technologies Inc.Amazon infooriginally Sqrrl Data, Inc.Mikio Hirabayashi
Initial release2013200120122020
Current release3.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemshostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
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 indexesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (SphinxQL)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocolAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesPython
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no
More information provided by the system vendor
DatabricksSphinxSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksSphinxSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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