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DBMS > QuestDB vs. Sadas Engine vs. SiriDB vs. Solr vs. Sphinx

System Properties Comparison QuestDB vs. Sadas Engine vs. SiriDB vs. Solr vs. Sphinx

Editorial information provided by DB-Engines
NameQuestDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSiriDB  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA high performance open source SQL database for time series dataSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen Source Time Series DBMSA widely used distributed, scalable search engine based on Apache LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSSearch engineSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitequestdb.iowww.sadasengine.comsiridb.comsolr.apache.orgsphinxsearch.com
Technical documentationquestdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.siridb.comsolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperQuestDB Technology IncSADAS s.r.l.CesbitApache Software FoundationSphinx Technologies Inc.
Initial release20142006201720062001
Current release8.09.5.0, February 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree trial version availableOpen Source infoMIT LicenseOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava (Zero-GC), C++, RustC++CJavaC++
Server operating systemsLinux
macOS
Windows
AIX
Linux
Windows
LinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyes infoschema-free via InfluxDB Line Protocolyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infoNumeric datayes infosupports customizable data types and automatic typingno
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.nononoyes
Secondary indexesnoyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL with time-series extensionsyesnoSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Proprietary protocol
HTTP APIJava API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnononoJava pluginsno
Triggersnononoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by timestamps)horizontal partitioningShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication with eventual consistencynoneyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID for single-table writesnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yes infothrough memory mapped filesyes infomanaged by 'Learn by Usage'yesyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardsimple rights management via user accountsyesno
More information provided by the system vendor
QuestDBSadas EngineSiriDBSolrSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
QuestDBSadas EngineSiriDBSolrSphinx
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