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DBMS > Apache IoTDB vs. Hazelcast vs. HBase vs. SurrealDB

System Properties Comparison Apache IoTDB vs. Hazelcast vs. HBase vs. SurrealDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHBase  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 FlinkA widely adopted in-memory data gridWide-column store based on Apache Hadoop and on concepts of BigTableA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelTime Series DBMSKey-value storeWide column storeDocument store
Graph DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websiteiotdb.apache.orghazelcast.comhbase.apache.orgsurrealdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docshbase.apache.org/­book.htmlsurrealdb.com/­docs
DeveloperApache Software FoundationHazelcastApache Software Foundation infoApache top-level project, originally developed by PowersetSurrealDB Ltd
Initial release2018200820082022
Current release1.1.0, April 20235.3.6, November 20232.3.4, January 2021v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache version 2Open Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaRust
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Data schemeyesschema-freeschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 infothe object must implement a serialization strategyno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenoSQL-like query language
APIs and other access methodsJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyes infoCoprocessors in Java
Triggersyesyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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 infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoone or two-phase-commit; repeatable reads; read commitedSingle row ACID (across millions of columns)ACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesRole-based access controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes, based on authentication and database rules

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Apache IoTDBHazelcastHBaseSurrealDB
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