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DBMS > Databend vs. IRONdb vs. Spark SQL vs. Sphinx vs. SQLite

System Properties Comparison Databend vs. IRONdb vs. Spark SQL vs. Sphinx vs. SQLite

Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonSQLite  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesWidely used embeddable, in-process RDBMS
Primary database modelRelational DBMSTime Series DBMSRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score114.32
Rank#10  Overall
#7  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.circonus.com/solutions/time-series-database/spark.apache.org/­sqlsphinxsearch.comwww.sqlite.org
Technical documentationdocs.databend.comdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.sqlite.org/­docs.html
DeveloperDatabend LabsCirconus LLC.Apache Software FoundationSphinx Technologies Inc.Dwayne Richard Hipp
Initial release20212017201420012000
Current release1.0.59, April 2023V0.10.20, January 20183.5.0 ( 2.13), September 20233.5.1, February 20233.46.0  (23 May 2024), May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoPublic Domain
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 languageRustC and C++ScalaC++C
Server operating systemshosted
Linux
macOS
LinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
server-less
Data schemeyesschema-freeyesyesyes infodynamic column types
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesnoyes infonot rigid because of 'dynamic typing' concept.
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.nononono
Secondary indexesnononoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes infoSQL-92 is not fully supported
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HTTP APIJDBC
ODBC
Proprietary protocolADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
Server-side scripts infoStored proceduresnoyes, in Luanonono
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodeyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter awarenonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infovia file-system locks
Durability infoSupport for making data persistentyesyesyesyes 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.nonoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnononono

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