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DBMS > AgensGraph vs. Google Cloud Datastore vs. ObjectBox vs. Tarantool

System Properties Comparison AgensGraph vs. Google Cloud Datastore vs. ObjectBox vs. Tarantool

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonObjectBox  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformExtremely fast embedded database for small devices, IoT and MobileIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelGraph DBMS
Relational DBMS
Document storeObject oriented DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitebitnine.net/­agensgraphcloud.google.com/­datastoreobjectbox.iowww.tarantool.io
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docsdocs.objectbox.iowww.tarantool.io/­en/­doc
DeveloperBitnine Global Inc.GoogleObjectBox LimitedVK
Initial release2016200820172008
Current release2.1, December 20182.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache License 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
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 languageCC and C++C and C++
Server operating systemsLinux
OS X
Windows
hostedAndroid
iOS
Linux
macOS
Windows
BSD
Linux
macOS
Data schemedepending on used data modelschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes, details hereyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noFull-featured ANSI SQL support
APIs and other access methodsCypher Query Language
JDBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary native APIOpen binary protocol
Supported programming languagesC
Java
JavaScript
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
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyesusing Google App EnginenoLua, C and SQL stored procedures
TriggersnoCallbacks using the Google Apps Enginenoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingnoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosonline/offline synchronization between client and serverAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
AgensGraphGoogle Cloud DatastoreObjectBoxTarantool
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More resources
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Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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