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DBMS > Apache IoTDB vs. BigchainDB vs. CrateDB vs. DuckDB

System Properties Comparison Apache IoTDB vs. BigchainDB vs. CrateDB vs. DuckDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonCrateDB  Xexclude from comparisonDuckDB  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 FlinkBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDistributed Database based on LuceneAn embeddable, in-process, column-oriented SQL OLAP RDBMS
Primary database modelTime Series DBMSDocument storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.79
Rank#212  Overall
#36  Document stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score4.57
Rank#74  Overall
#40  Relational DBMS
Websiteiotdb.apache.orgwww.bigchaindb.comcratedb.comduckdb.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlbigchaindb.readthedocs.io/­en/­latestcratedb.com/­docsduckdb.org/­docs
DeveloperApache Software FoundationCrate
Initial release2018201620132018
Current release1.1.0, April 20230.10, February 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL v3Open SourceOpen Source infoMIT License
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.
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 languageJavaPythonJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportserver-less
Data schemeyesschema-freeFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes, but no triggers and constraints, and PostgreSQL compatibilityyes
APIs and other access methodsJDBC
Native API
CLI Client
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Haskell
Java
JavaScript
Python
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
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)no
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factorConfigurable replication on table/partition-levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
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 Consistency
Foreign keys infoReferential integritynononono
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 strategyACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlyesyesrights management via user accountsno
More information provided by the system vendor
Apache IoTDBBigchainDBCrateDBDuckDB
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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Apache IoTDBBigchainDBCrateDBDuckDB
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