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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. Rockset vs. STSdb vs. Vitess

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. Rockset vs. STSdb vs. Vitess

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonRockset  Xexclude from comparisonSTSdb  Xexclude from comparisonVitess  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.A scalable, reliable search and analytics service in the cloud, built on RocksDBKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument storeTime Series DBMSDocument storeKey-value storeRelational DBMS
Secondary database modelsRelational DBMS
Search engine
Document store
Spatial 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
Score0.79
Rank#211  Overall
#35  Document stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecloud.google.com/­datastorewww.hawkular.orgrockset.comgithub.com/­STSSoft/­STSdb4vitess.io
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.rockset.comvitess.io/­docs
DeveloperGoogleCommunity supported by Red HatRocksetSTS Soft SCThe Linux Foundation, PlanetScale
Initial release20082014201920112013
Current release4.0.8, September 201515.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoGPLv2, commercial license availableOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C#Go
Server operating systemshostedLinux
OS X
Windows
hostedWindowsDocker
Linux
macOS
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes, details hereyesdynamic typingyes infoprimitive types and user defined types (classes)yes
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 infoingestion from XML files supported
Secondary indexesyesnoall fields are automatically indexednoyes
SQL infoSupport of SQLSQL-like query language (GQL)noRead-only SQL queries, including JOINsnoyes infowith proprietary extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTHTTP REST.NET Client APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C#
Java
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 proceduresusing Google App Enginenononoyes infoproprietary syntax
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraAutomatic shardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandrayesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnononoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users and organizations can be defined via Rockset consolenoUsers with fine-grained authorization concept infono user groups or roles

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More resources
Google Cloud DatastoreHawkular MetricsRocksetSTSdbVitess
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