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DBMS > Google Cloud Bigtable vs. Hawkular Metrics vs. Kdb vs. PlanetScale

System Properties Comparison Google Cloud Bigtable vs. Hawkular Metrics vs. Kdb vs. PlanetScale

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKdb  Xexclude from comparisonPlanetScale  Xexclude from comparison
DescriptionGoogle'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.High performance Time Series DBMSScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelKey-value store
Wide column store
Time Series DBMSTime Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score7.73
Rank#45  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score1.09
Rank#178  Overall
#82  Relational DBMS
Websitecloud.google.com/­bigtablewww.hawkular.orgkx.complanetscale.com
Technical documentationcloud.google.com/­bigtable/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidecode.kx.complanetscale.com/­docs
DeveloperGoogleCommunity supported by Red HatKx Systems, a division of First Derivatives plcPlanetScale
Initial release201520142000 infokdb was released 2000, kdb+ in 20032020
Current release3.6, May 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree 32-bit versioncommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaqGo
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonoyes
Secondary indexesnonoyes infotable attribute 'grouped'yes
SQL infoSupport of SQLnonoSQL-like query language (q)yes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP RESTHTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonouser defined functionsyes infoproprietary syntax
Triggersnoyes infovia Hawkular Alertingyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrahorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on CassandraSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono infosimilar paradigm used for internal processingno
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)norights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Google Cloud BigtableHawkular MetricsKdbPlanetScale
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Google Cloud BigtableHawkular MetricsKdbPlanetScale
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