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DBMS > Drizzle vs. Google Cloud Datastore vs. Hawkular Metrics vs. Riak TS

System Properties Comparison Drizzle vs. Google Cloud Datastore vs. Hawkular Metrics vs. Riak TS

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonRiak TS  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 PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMSDocument storeTime Series DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websitecloud.google.com/­datastorewww.hawkular.org
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperDrizzle project, originally started by Brian AkerGoogleCommunity supported by Red HatOpen Source, formerly Basho Technologies
Initial release2008200820142015
Current release7.2.4, September 20123.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0Open Source
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++JavaErlang
Server operating systemsFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Linux
OS X
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesno
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 indexesyesyesnorestricted
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like query language (GQL)noyes, limited
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP API
Native Erlang Interface
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnousing Google App EnginenoErlang
Triggersno infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyes infovia Hawkular Alertingyes infopre-commit hooks and post-commit hooks
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
Multi-source replication using Paxosselectable replication factor infobased on Cassandraselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
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.nono
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)nono

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More resources
DrizzleGoogle Cloud DatastoreHawkular MetricsRiak TS
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