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DBMS > Google Cloud Datastore vs. Hawkular Metrics vs. NSDb vs. Spark SQL

System Properties Comparison Google Cloud Datastore vs. Hawkular Metrics vs. NSDb vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonNSDb  Xexclude from comparisonSpark SQL  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.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeTime Series DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecloud.google.com/­datastorewww.hawkular.orgnsdb.iospark.apache.org/­sql
Technical documentationcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidensdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleCommunity supported by Red HatApache Software Foundation
Initial release2008201420172014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ScalaScala
Server operating systemshostedLinux
OS X
Windows
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesyes: int, bigint, decimal, stringyes
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.nononono
Secondary indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTgRPC
HTTP REST
WebSocket
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresusing Google App Enginenonono
TriggersCallbacks using the Google Apps Engineyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosselectable replication factor infobased on Cassandranone
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
Eventual 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 Transactionsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Google Cloud DatastoreHawkular MetricsNSDbSpark SQL
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