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DBMS > Apache IoTDB vs. eXtremeDB vs. Sphinx vs. SurrealDB

System Properties Comparison Apache IoTDB vs. eXtremeDB vs. Sphinx vs. SurrealDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonSphinx  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkNatively in-memory DBMS with options for persistency, high-availability and clusteringOpen source search engine for searching in data from different sources, e.g. relational databasesA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelTime Series DBMSRelational DBMS
Time Series DBMS
Search engineDocument store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Websiteiotdb.apache.orgwww.mcobject.comsphinxsearch.comsurrealdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.mcobject.com/­docs/­extremedb.htmsphinxsearch.com/­docssurrealdb.com/­docs
DeveloperApache Software FoundationMcObjectSphinx Technologies Inc.SurrealDB Ltd
Initial release2018200120012022
Current release1.1.0, April 20238.2, 20213.5.1, February 2023v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++Rust
Server operating systemsAll OS with a Java VM (>= 1.8)AIX
HP-UX
Linux
macOS
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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 infosupport of XML interfaces available
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyes infowith the option: eXtremeSQLSQL-like query language (SphinxQL)SQL-like query language
APIs and other access methodsJDBC
Native API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Proprietary protocolGraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresyesyesno
Triggersyesyes infoby defining eventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioning / shardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
Durability infoSupport for making data persistentyesyesyes 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.yesyes
User concepts infoAccess controlyesnoyes, based on authentication and database rules
More information provided by the system vendor
Apache IoTDBeXtremeDBSphinxSurrealDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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Apache IoTDBeXtremeDBSphinxSurrealDB
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