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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. TDSQL for MySQL vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. TDSQL for MySQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.Platform for big data analytics on multistructured data sources and types
Primary database modelDocument storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.96
Rank#192  Overall
#88  Relational DBMS
Websitecloud.google.com/­datastorewww.hawkular.orgwww.tencentcloud.com/­products/­dcdb
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.tencentcloud.com/­document/­product/­1042
DeveloperGoogleCommunity supported by Red HatTencentTeradata
Initial release2008201420132005
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedLinux
OS X
Windows
hostedLinux
Data schemeschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes, details hereyesyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noyesyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C
C#
C++
Java
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App EnginenoyesR packages
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes infoSQL Map-Reduce Framework
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
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 TransactionsnoACIDACID
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHawkular MetricsTDSQL for MySQLTeradata Aster
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