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DBMS > Apache Phoenix vs. Cloudflare Workers KV vs. CrateDB vs. InfinityDB

System Properties Comparison Apache Phoenix vs. Cloudflare Workers KV vs. CrateDB vs. InfinityDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonCrateDB  Xexclude from comparisonInfinityDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Distributed Database based on LuceneA Java embedded Key-Value Store which extends the Java Map interface
Primary database modelRelational DBMSKey-value storeDocument 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.32
Rank#283  Overall
#40  Key-value stores
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Websitephoenix.apache.orgwww.cloudflare.com/­developer-platform/­workers-kvcratedb.comboilerbay.com
Technical documentationphoenix.apache.orgdevelopers.cloudflare.com/­kv/­apicratedb.com/­docsboilerbay.com/­infinitydb/­manual
DeveloperApache Software FoundationCloudflareCrateBoiler Bay Inc.
Initial release2014201820132002
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJavaJavaJava
Server operating systemsLinux
Unix
Windows
hostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VM
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade
Typing infopredefined data types such as float or dateyesnoyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arrays
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 indexesyesnoyesno infomanual creation possible, using inversions based on multi-value capability
SQL infoSupport of SQLyesnoyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsJDBCHTTP REST
Proprietary protocol
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Dart
JavaScript
Kotlin
Python
Rust
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
Java
Server-side scripts infoStored proceduresuser defined functionsnouser defined functions (Javascript)no
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesConfigurable 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 ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynononono infomanual creation possible, using inversions based on multi-value capability
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoOptimistic locking for transactions; no isolation for bulk loads
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 controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyrights management via user accountsno
More information provided by the system vendor
Apache PhoenixCloudflare Workers KVCrateDBInfinityDB
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 PhoenixCloudflare Workers KVCrateDBInfinityDB
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