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DBMS > Apache IoTDB vs. CrateDB vs. Greenplum vs. VictoriaMetrics

System Properties Comparison Apache IoTDB vs. CrateDB vs. Greenplum vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCrateDB  Xexclude from comparisonGreenplum  Xexclude from comparisonVictoriaMetrics  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 FlinkDistributed Database based on LuceneAnalytic 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.A fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSTime Series DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteiotdb.apache.orgcratedb.comgreenplum.orgvictoriametrics.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcratedb.com/­docsdocs.greenplum.orgdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software FoundationCratePivotal Software Inc.VictoriaMetrics
Initial release2018201320052018
Current release1.1.0, April 20237.0.0, September 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0
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 languageJavaJavaGo
Server operating systemsAll OS with a Java VM (>= 1.8)All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxFreeBSD
Linux
macOS
OpenBSD
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyesyes
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 4.2no
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilityyesno
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
Java
Perl
Python
R
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)yesno
Triggersyesnoyesno
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 replicasConfigurable replication on table/partition-levelSource-replica replicationSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDno
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.yesnonono
User concepts infoAccess controlyesrights management via user accountsfine grained access rights according to SQL-standard

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More resources
Apache IoTDBCrateDBGreenplumVictoriaMetrics
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