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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigchainDB  Xexclude from comparisonCrateDB  Xexclude from comparisonDuckDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsDistributed Database based on LuceneAn embeddable, in-process, column-oriented SQL OLAP RDBMS
Primary database modelRelational 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
Score1.97
Rank#126  Overall
#59  Relational 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
Websitephoenix.apache.orgwww.bigchaindb.comcratedb.comduckdb.org
Technical documentationphoenix.apache.orgbigchaindb.readthedocs.io/­en/­latestcratedb.com/­docsduckdb.org/­docs
DeveloperApache Software FoundationCrate
Initial release2014201620132018
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.10, 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 systemsLinux
Unix
Windows
LinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportserver-less
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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 SQLyesnoyes, but no triggers and constraints, and PostgreSQL compatibilityyes
APIs and other access methodsJDBCCLI 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
Groovy
Java
PHP
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 proceduresuser defined functionsuser defined functions (Javascript)no
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factorConfigurable replication on table/partition-levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual 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 dataACIDno 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 controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyesrights management via user accountsno
More information provided by the system vendor
Apache PhoenixBigchainDBCrateDBDuckDB
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 PhoenixBigchainDBCrateDBDuckDB
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
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