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DBMS > Drizzle vs. Google Cloud Bigtable vs. Hawkular Metrics vs. HBase

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Hawkular Metrics vs. HBase

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMSKey-value store
Wide column store
Time Series DBMSWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Websitecloud.google.com/­bigtablewww.hawkular.orghbase.apache.org
Technical documentationcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.html
DeveloperDrizzle project, originally started by Brian AkerGoogleCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2008201520142008
Current release7.2.4, September 20122.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0Open Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJava
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
Data schemeyesschema-freeschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesnoyesoptions to bring your own types, AVRO
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 indexesyesnonono
SQL infoSupport of SQLyes infowith proprietary extensionsnonono
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTJava API
RESTful HTTP API
Thrift
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresnononoyes infoCoprocessors in Java
Triggersno infohooks for callbacks inside the server can be used.noyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoSingle row ACID (across millions of columns)
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.nonoyes
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)noAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources
DrizzleGoogle Cloud BigtableHawkular MetricsHBase
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