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DBMS > Apache Phoenix vs. CrateDB vs. KeyDB

System Properties Comparison Apache Phoenix vs. CrateDB vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCrateDB  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Database based on LuceneAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitephoenix.apache.orgcratedb.comgithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationphoenix.apache.orgcratedb.com/­docsdocs.keydb.dev
DeveloperApache Software FoundationCrateEQ Alpha Technology Ltd.
Initial release201420132019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenonono
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 languageJavaJavaC++
Server operating systemsLinux
Unix
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.nonono
Secondary indexesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
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
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresuser defined functionsuser defined functions (Javascript)Lua
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Configurable replication on table/partition-levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynonono
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 strategyOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
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-tenancyrights management via user accountssimple password-based access control and ACL
More information provided by the system vendor
Apache PhoenixCrateDBKeyDB
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 PhoenixCrateDBKeyDB
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