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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGridGain  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 FlinkGridGain is an in-memory computing platform, built on Apache IgniteOpen 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 DBMSKey-value store
Relational 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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Websiteiotdb.apache.orgwww.gridgain.comsphinxsearch.comsurrealdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docssurrealdb.com/­docs
DeveloperApache Software FoundationGridGain Systems, Inc.Sphinx Technologies Inc.SurrealDB Ltd
Initial release2018200720012022
Current release1.1.0, April 2023GridGain 8.5.13.5.1, 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

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Implementation languageJavaJava, C++, .NetC++Rust
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
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.noyes
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)SQL-like query language
APIs and other access methodsJDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolGraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
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 proceduresyesyes (compute grid and cache interceptors can be used instead)no
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)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 replicasyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 controlyesSecurity Hooks for custom implementationsnoyes, based on authentication and database rules

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More resources
Apache IoTDBGridGainSphinxSurrealDB
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