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DBMS > atoti vs. Google Cloud Datastore vs. GridGain vs. Stardog

System Properties Comparison atoti vs. Google Cloud Datastore vs. GridGain vs. Stardog

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridGain  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformGridGain is an in-memory computing platform, built on Apache IgniteEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelObject oriented DBMSDocument storeKey-value store
Relational DBMS
Graph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteatoti.iocloud.google.com/­datastorewww.gridgain.comwww.stardog.com
Technical documentationdocs.atoti.iocloud.google.com/­datastore/­docswww.gridgain.com/­docs/­index.htmldocs.stardog.com
DeveloperActiveViamGoogleGridGain Systems, Inc.Stardog-Union
Initial release200820072010
Current releaseGridGain 8.5.17.3.0, May 2020
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeyesschema-free and OWL/RDFS-schema support
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.noyesno infoImport/export of XML data possible
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDLYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresPythonusing Google App Engineyes (compute grid and cache interceptors can be used instead)user defined functions and aggregates, HTTP Server extensions in Java
TriggersCallbacks using the Google Apps Engineyes (cache interceptors and events)yes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes (replicated cache)Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
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 ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsAccess rights for users and roles

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More resources
atotiGoogle Cloud DatastoreGridGainStardog
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