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

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

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonQuasardb  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.Distributed, high-performance timeseries database
Primary database modelRelational DBMSKey-value storeKey-value store
Wide column store
Time Series 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
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitegeode.apache.orgcloud.google.com/­bigtablequasar.ai
Technical documentationgeode.apache.org/­docscloud.google.com/­bigtable/­docsdoc.quasar.ai/­master
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.Googlequasardb
Initial release2008200220152009
Current release7.2.4, September 20121.1, February 20173.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredhostedBSD
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes infointeger and binary
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 infowith tags
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (OQL)noSQL-like query language
APIs and other access methodsJDBCJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Supported programming languagesC
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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 infoconsistent hashing
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 zonesSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyeswith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient mode
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)Cryptographically strong user authentication and audit trail

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DrizzleGeodeGoogle Cloud BigtableQuasardb
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