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DBMS > Amazon DocumentDB vs. Drizzle vs. HEAVY.AI vs. Kinetica vs. WakandaDB

System Properties Comparison Amazon DocumentDB vs. Drizzle vs. HEAVY.AI vs. Kinetica vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDrizzle  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonWakandaDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.80
Rank#148  Overall
#25  Document stores
Score2.30
Rank#127  Overall
#60  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score0.06
Rank#374  Overall
#17  Object oriented DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwakanda.github.io
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.heavy.aidocs.kinetica.comwakanda.github.io/­doc
DeveloperDrizzle project, originally started by Brian AkerHEAVY.AI, Inc.KineticaWakanda SAS
Initial release20192008201620122012
Current release7.2.4, September 20125.10, January 20227.1, August 20212.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ and CUDAC, C++C++, JavaScript
Server operating systemshostedFreeBSD
Linux
OS X
LinuxLinuxLinux
OS X
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsyesSQL-like DML and DDL statementsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Java
PHP
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresnononouser defined functionsyes
Triggersnono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
Multi-source replicationSource-replica 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 ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyes

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More resources
Amazon DocumentDBDrizzleHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaWakandaDB
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