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DBMS > Apache IoTDB vs. Axibase vs. CrateDB vs. HugeGraph

System Properties Comparison Apache IoTDB vs. Axibase vs. CrateDB vs. HugeGraph

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAxibase  Xexclude from comparisonCrateDB  Xexclude from comparisonHugeGraph  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 FlinkScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationDistributed Database based on LuceneA fast-speed and highly-scalable Graph DBMS
Primary database modelTime Series DBMSTime Series DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Graph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteiotdb.apache.orgaxibase.com/­docs/­atsd/­financecratedb.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcratedb.com/­docshugegraph.apache.org/­docs
DeveloperApache Software FoundationAxibase CorporationCrateBaidu
Initial release2018201320132018
Current release1.1.0, April 2023155850.9
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen SourceOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaJavaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
macOS
Unix
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringyesyes
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.nononono
Secondary indexesyesnoyesyes infoalso supports composite index and range index
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsJDBC
Native API
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
PHP
Python
R
Ruby
.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
Groovy
Java
Python
Server-side scripts infoStored proceduresyesyesuser defined functions (Javascript)asynchronous Gremlin script jobs
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
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 replicationConfigurable replication on table/partition-levelyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesnovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Foreign keys infoReferential integritynononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
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.yesnoyes
User concepts infoAccess controlyesrights management via user accountsUsers, roles and permissions
More information provided by the system vendor
Apache IoTDBAxibaseCrateDBHugeGraph
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
Apache IoTDBAxibaseCrateDBHugeGraph
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