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DBMS > Drizzle vs. Google Cloud Datastore vs. HEAVY.AI vs. Kinetica vs. Netezza

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. HEAVY.AI vs. Kinetica vs. Netezza

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitecloud.google.com/­datastoregithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwww.ibm.com/­products/­netezza
Technical documentationcloud.google.com/­datastore/­docsdocs.heavy.aidocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerGoogleHEAVY.AI, Inc.KineticaIBM
Initial release20082008201620122000
Current release7.2.4, September 20125.10, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ and CUDAC, C++
Server operating systemsFreeBSD
Linux
OS X
hostedLinuxLinuxLinux infoincluded in appliance
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyesyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)yesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functionsyes
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replicationSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
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.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users and roles on table levelUsers with fine-grained authorization concept

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More resources
DrizzleGoogle Cloud DatastoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaNetezza infoAlso called PureData System for Analytics by IBM
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