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DBMS > Google Cloud Datastore vs. Hazelcast vs. Sqrrl vs. Teradata Aster vs. Valentina Server

System Properties Comparison Google Cloud Datastore vs. Hazelcast vs. Sqrrl vs. Teradata Aster vs. Valentina Server

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonSqrrl  Xexclude from comparisonTeradata Aster  Xexclude from comparisonValentina Server  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.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 PlatformA widely adopted in-memory data gridAdaptable, secure NoSQL built on Apache AccumuloPlatform for big data analytics on multistructured data sources and typesObject-relational database and reports server
Primary database modelDocument storeKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitecloud.google.com/­datastorehazelcast.comsqrrl.comwww.valentina-db.net
Technical documentationcloud.google.com/­datastore/­docshazelcast.org/­imdg/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperGoogleHazelcastAmazon infooriginally Sqrrl Data, Inc.TeradataParadigma Software
Initial release20082008201220051999
Current release5.3.6, November 20235.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemshostedAll OS with a Java VMLinuxLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyesyes
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.noyes infothe object must implement a serialization strategyyes infoin Aster File Store
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languagenoyesyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
OLE DB
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Java
Python
R
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresusing Google App Engineyes infoEvent Listeners, Executor ServicesnoR packagesyes
TriggersCallbacks using the Google Apps Engineyes infoEventsnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoReplicated Mapselectable replication factor infomaking use of Hadoopyes 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 Dataflowyesyesyes infoSQL Map-Reduce Frameworkno
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.Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitedAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHazelcastSqrrlTeradata AsterValentina Server
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