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DBMS > Cloudflare Workers KV vs. CrateDB vs. ObjectBox vs. Sphinx

System Properties Comparison Cloudflare Workers KV vs. CrateDB vs. ObjectBox vs. Sphinx

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Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonCrateDB  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Distributed Database based on LuceneExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Object oriented DBMSSearch engine
Secondary database modelsRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.cloudflare.com/­developer-platform/­workers-kvcratedb.comobjectbox.iosphinxsearch.com
Technical documentationdevelopers.cloudflare.com/­kv/­apicratedb.com/­docsdocs.objectbox.iosphinxsearch.com/­docs
DeveloperCloudflareCrateObjectBox LimitedSphinx Technologies Inc.
Initial release2018201320172001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
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 languageJavaC and C++C++
Server operating systemshostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or datenoyesyesno
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 indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL-like query language (SphinxQL)
APIs and other access methodsHTTP REST
Proprietary protocol
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Proprietary native APIProprietary protocol
Supported programming languagesC
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
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions (Javascript)nono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelonline/offline synchronization between client and servernone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
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 strategyACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlrights management via user accountsyesno
More information provided by the system vendor
Cloudflare Workers KVCrateDBObjectBoxSphinx
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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