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DBMS > QuestDB vs. Sadas Engine vs. Sphinx

System Properties Comparison QuestDB vs. Sadas Engine vs. Sphinx

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Editorial information provided by DB-Engines
NameQuestDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA high performance, low latency Time Series DBMSSADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environmentsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSRelational DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#266  Overall
#20  Time Series DBMS
Score0.09
Rank#307  Overall
#130  Relational DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Websitequestdb.iowww.sadasengine.comsphinxsearch.com
Technical documentationquestdb.io/­docs/­introductionwww.sadasengine.com/­index.php/­downloads/­documentation-columnar-dbsphinxsearch.com/­docs
DeveloperQuestDB LimitedSADAS s.r.l.Sphinx Technologies Inc.
Initial release201420062001
Current release8.03.2.1, January 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree trial version availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
macOS
Windows
AIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesno
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.nono
Secondary indexesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyesSQL-like query language (SphinxQL)
APIs and other access methodsHTTP RESTJDBC
ODBC
Proprietary protocol
Proprietary protocol
Supported programming languagesJava.Net
C
C#
C++
Groovy
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by timestamps)horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID for single-table writesno
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 infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
QuestDBSadas EngineSphinx
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more

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QuestDBSadas EngineSphinx
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