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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. OpenQM vs. TDengine

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. OpenQM vs. TDengine

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonTDengine  Xexclude from comparison
DescriptionAutomatically 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.QpenQM is a high-performance, self-tuning, multi-value DBMSTime Series DBMS and big data platform
Primary database modelDocument storeTime Series DBMSMultivalue DBMSTime Series DBMS
Secondary database modelsRelational 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
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Score2.60
Rank#107  Overall
#8  Time Series DBMS
Websitecloud.google.com/­datastorewww.hawkular.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.tdengine.com
DeveloperGoogleCommunity supported by Red HatRocket Software, originally Martin PhillipsTDEngine, previously Taos Data
Initial release2008201419932019
Current release3.4-123.0, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPLv2, extended commercial license availableOpen Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemshostedLinux
OS X
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Linux
Windows
Data schemeschema-freeschema-freeyes infowith some exceptionsyes
Typing infopredefined data types such as float or dateyes, details hereyesyes
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.nonoyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL-like query language (GQL)nonoStandard SQL with extensions for time-series applications
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJDBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
Basic
C
Java
Objective C
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresusing Google App Enginenoyesno
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandrayesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandrayesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
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
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
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 controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights can be defined down to the item levelyes
More information provided by the system vendor
Google Cloud DatastoreHawkular MetricsOpenQM infoalso called QMTDengine
Specific characteristicsTDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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