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DBMS > Amazon DocumentDB vs. Cloudflare Workers KV vs. Cubrid vs. HEAVY.AI vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Cloudflare Workers KV vs. Cubrid vs. HEAVY.AI vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonCubrid  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.CUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeKey-value storeRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.39
Rank#274  Overall
#39  Key-value stores
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbwww.cloudflare.com/­developer-platform/­workers-kvcubrid.com (korean)
cubrid.org (english)
github.com/­heavyai/­heavydb
www.heavy.ai
sphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdevelopers.cloudflare.com/­kv/­apicubrid.org/­manualsdocs.heavy.aisphinxsearch.com/­docs
DeveloperCloudflareCUBRID Corporation, CUBRID FoundationHEAVY.AI, Inc.Sphinx Technologies Inc.
Initial release20192018200820162001
Current release11.0, January 20215.10, January 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaC++ and CUDAC++
Server operating systemshostedhostedLinux
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesno
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 indexesyesnoyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyesyesSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HTTP REST
Proprietary protocol
ADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
Thrift
Vega
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoJava Stored Proceduresnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoRound robinSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesSource-replica replicationMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonoyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Amazon DocumentDBCloudflare Workers KVCubridHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Sphinx
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