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DBMS > Databricks vs. mSQL vs. PouchDB vs. Sphinx vs. TimescaleDB

System Properties Comparison Databricks vs. mSQL vs. PouchDB vs. Sphinx vs. TimescaleDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonPouchDB  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  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.mSQL (Mini SQL) is a simple and lightweight RDBMSJavaScript DBMS with an API inspired by CouchDBOpen source search engine for searching in data from different sources, e.g. relational databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeSearch engineTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.databricks.comhughestech.com.au/­products/­msqlpouchdb.comsphinxsearch.comwww.timescale.com
Technical documentationdocs.databricks.compouchdb.com/­guidessphinxsearch.com/­docsdocs.timescale.com
DeveloperDatabricksHughes TechnologiesApache Software FoundationSphinx Technologies Inc.Timescale
Initial release20131994201220012017
Current release4.4, October 20217.1.1, June 20193.5.1, February 20232.13.0, November 2023
License infoCommercial or Open Sourcecommercialcommercial infofree licenses can be providedOpen SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaScriptC++C
Server operating systemshostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
server-less, requires a JavaScript environment (browser, Node.js)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnononumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnonoyes
Secondary indexesyesyesyes infovia viewsyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C
C++
Delphi
Java
Perl
PHP
Tcl
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoView functions in JavaScriptnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infowith a proxy-based framework, named couchdb-loungeSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes 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.nonoyesno
User concepts infoAccess controlnononofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksmSQL infoMini SQLPouchDBSphinxTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksmSQL infoMini SQLPouchDBSphinxTimescaleDB
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