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DBMS > atoti vs. Dgraph vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. ObjectBox

System Properties Comparison atoti vs. Dgraph vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. ObjectBox

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDgraph  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonObjectBox  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Distributed and scalable native Graph DBMSGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformExtremely fast embedded database for small devices, IoT and Mobile
Primary database modelObject oriented DBMSGraph DBMSKey-value store
Wide column store
Document storeObject oriented DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.36
Rank#72  Overall
#12  Document stores
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websiteatoti.iodgraph.iocloud.google.com/­bigtablecloud.google.com/­datastoreobjectbox.io
Technical documentationdocs.atoti.iodgraph.io/­docscloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsdocs.objectbox.io
DeveloperActiveViamDgraph Labs, Inc.GoogleGoogleObjectBox Limited
Initial release2016201520082017
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0commercialcommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoC and C++
Server operating systemsLinux
OS X
Windows
hostedhostedAndroid
iOS
Linux
macOS
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes, details hereyes
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 indexesyesnoyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)nonoSQL-like query language (GQL)no
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary native API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Server-side scripts infoStored proceduresPythonnonousing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningyesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication using Paxosonline/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate 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
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
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.yesnonono
User concepts infoAccess controlno infoPlanned for future releasesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes
More information provided by the system vendor
atotiDgraphGoogle Cloud BigtableGoogle Cloud DatastoreObjectBox
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atotiDgraphGoogle Cloud BigtableGoogle Cloud DatastoreObjectBox
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