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DBMS > Drizzle vs. Hawkular Metrics vs. Pinecone vs. ReductStore

System Properties Comparison Drizzle vs. Hawkular Metrics vs. Pinecone vs. ReductStore

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPinecone  Xexclude from comparisonReductStore  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.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A managed, cloud-native vector databaseDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSTime Series DBMSVector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websitewww.hawkular.orgwww.pinecone.iogithub.com/­reductstore
www.reduct.store
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.pinecone.io/­docs/­overviewwww.reduct.store/­docs
DeveloperDrizzle project, originally started by Brian AkerCommunity supported by Red HatPinecone Systems, IncReductStore LLC
Initial release2008201420192023
Current release7.2.4, September 20121.9, March 2024
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0commercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++, Rust
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
hostedDocker
Linux
macOS
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesyesString, Number, Boolean
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.nono
Secondary indexesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsnono
APIs and other access methodsJDBCHTTP RESTRESTful HTTP APIHTTP API
Supported programming languagesC
C++
Java
PHP
Go
Java
Python
Ruby
PythonC++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnono
Triggersno infohooks for callbacks inside the server can be used.yes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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, HTTPno

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More resources
DrizzleHawkular MetricsPineconeReductStore
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