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DBMS > Bangdb vs. Google Cloud Datastore vs. ObjectBox vs. TigerGraph

System Properties Comparison Bangdb vs. Google Cloud Datastore vs. ObjectBox vs. TigerGraph

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonObjectBox  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformExtremely fast embedded database for small devices, IoT and MobileA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeObject oriented DBMSGraph DBMS
Secondary database modelsSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitebangdb.comcloud.google.com/­datastoreobjectbox.iowww.tigergraph.com
Technical documentationdocs.bangdb.comcloud.google.com/­datastore/­docsdocs.objectbox.iodocs.tigergraph.com
DeveloperSachin Sinha, BangDBGoogleObjectBox Limited
Initial release2012200820172017
Current releaseBangDB 2.0, October 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache License 2.0commercial
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 languageC, C++C and C++C++
Server operating systemsLinuxhostedAndroid
iOS
Linux
macOS
Windows
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes, 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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like query language (GQL)noSQL-like query language (GSQL)
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary native APIGSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
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++
Java
Server-side scripts infoStored proceduresnousing Google App Enginenoyes
Triggersyes, Notifications (with Streaming only)Callbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication using Paxosonline/offline synchronization between client and server
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate 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 integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenonono
User concepts infoAccess controlyes (enterprise version only)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesRole-based access control
More information provided by the system vendor
BangdbGoogle Cloud DatastoreObjectBoxTigerGraph
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BangdbGoogle Cloud DatastoreObjectBoxTigerGraph
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