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DBMS > Drizzle vs. EXASOL vs. Geode vs. Google Cloud Datastore vs. Kinetica

System Properties Comparison Drizzle vs. EXASOL vs. Geode vs. Google Cloud Datastore vs. Kinetica

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonEXASOL  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score1.99
Rank#133  Overall
#23  Key-value stores
Score4.49
Rank#79  Overall
#12  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websitewww.exasol.comgeode.apache.orgcloud.google.com/­datastorewww.kinetica.com
Technical documentationwww.exasol.com/­resourcesgeode.apache.org/­docscloud.google.com/­datastore/­docsdocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerExasolOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleKinetica
Initial release20082000200220082012
Current release7.2.4, September 20121.1, February 20177.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC, C++
Server operating systemsFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes, details hereyes
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 indexesyesyesnoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsyesSQL-like query language (OQL)SQL-like query language (GQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC.Net
JDBC
ODBC
WebSocket
Java Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
Java
Lua
Python
R
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsusing Google App Engineuser defined functions
Triggersno infohooks for callbacks inside the server can be used.yesyes infoCache Event ListenersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationMulti-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate 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 Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.yesyesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles according to SQL-standardAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level

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More resources
DrizzleEXASOLGeodeGoogle Cloud DatastoreKinetica
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