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DBMS > Apache IoTDB vs. Graph Engine vs. Greenplum vs. HBase vs. QuestDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. Greenplum vs. HBase vs. QuestDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonGreenplum  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  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 distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Wide-column store based on Apache Hadoop and on concepts of BigTableA high performance open source SQL database for time series data
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMSWide column storeTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websiteiotdb.apache.orgwww.graphengine.iogreenplum.orghbase.apache.orgquestdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.graphengine.io/­docs/­manualdocs.greenplum.orghbase.apache.org/­book.htmlquestdb.io/­docs
DeveloperApache Software FoundationMicrosoftPivotal Software Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology Inc
Initial release20182010200520082014
Current release1.1.0, April 20237.0.0, September 20232.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache 2.0
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.NET and CJavaJava (Zero-GC), C++, Rust
Server operating systemsAll OS with a Java VM (>= 1.8).NETLinuxLinux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Data schemeyesyesyesschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyesoptions 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.nonoyes infosince Version 4.2nono
Secondary indexesyesyesnono
SQL infoSupport of SQLSQL-like query languagenoyesnoSQL with time-series extensions
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
Java API
RESTful HTTP API
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
F#
Visual Basic
C
Java
Perl
Python
R
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresyesyesyesyes infoCoprocessors in Javano
Triggersyesnoyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication with eventual consistency
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 ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDSingle row ACID (across millions of columns)ACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes infothrough memory mapped files
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
Apache IoTDBGraph Engine infoformer name: TrinityGreenplumHBaseQuestDB
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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