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DBMS > Databricks vs. Drizzle vs. GridDB vs. Hawkular Metrics vs. KairosDB

System Properties Comparison Databricks vs. Drizzle vs. GridDB vs. Hawkular Metrics vs. KairosDB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKairosDB  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.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Scalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Distributed Time Series DBMS based on Cassandra or H2
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.67
Rank#233  Overall
#20  Time Series DBMS
Websitewww.databricks.comgriddb.netwww.hawkular.orggithub.com/­kairosdb/­kairosdb
Technical documentationdocs.databricks.comdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidekairosdb.github.io
DeveloperDatabricksDrizzle project, originally started by Brian AkerToshiba CorporationCommunity supported by Red Hat
Initial release20132008201320142013
Current release7.2.4, September 20125.1, August 20221.2.2, November 2018
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++JavaJava
Server operating systemshostedFreeBSD
Linux
OS X
LinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.yesnonono
Secondary indexesyesyesyesnono
SQL infoSupport of SQLwith Databricks SQLyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTGraphite protocol
HTTP REST
Telnet API
Supported programming languagesPython
R
Scala
C
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnononono
Triggersno infohooks for callbacks inside the server can be used.yesyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replicationselectable replication factor infobased on Cassandraselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databasenosimple password-based access control
More information provided by the system vendor
DatabricksDrizzleGridDBHawkular MetricsKairosDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
DatabricksDrizzleGridDBHawkular MetricsKairosDB
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