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DBMS > Drizzle vs. Geode vs. Google Cloud Bigtable vs. JaguarDB

System Properties Comparison Drizzle vs. Geode vs. Google Cloud Bigtable vs. JaguarDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonJaguarDB  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.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Performant, highly scalable DBMS for AI and IoT applications
Primary database modelRelational DBMSKey-value storeKey-value store
Wide column store
Key-value store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Websitegeode.apache.orgcloud.google.com/­bigtablewww.jaguardb.com
Technical documentationgeode.apache.org/­docscloud.google.com/­bigtable/­docswww.jaguardb.com/­support.html
DeveloperDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleDataJaguar, Inc.
Initial release2008200220152015
Current release7.2.4, September 20121.1, February 20173.3 July 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++ infothe server part. Clients available in other languages
Server operating systemsFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesnonoyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (OQL)noA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsJDBCJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languagesC
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersno infohooks for callbacks inside the server can be used.yes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accounts

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More resources
DrizzleGeodeGoogle Cloud BigtableJaguarDB
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