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DBMS > BigObject vs. Databend vs. Dgraph vs. GridDB vs. SwayDB

System Properties Comparison BigObject vs. Databend vs. Dgraph vs. GridDB vs. SwayDB

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDatabend  Xexclude from comparisonDgraph  Xexclude from comparisonGridDB  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityDistributed and scalable native Graph DBMSScalable in-memory time series database optimized for IoT and Big DataAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSGraph DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitebigobject.iogithub.com/­datafuselabs/­databend
www.databend.com
dgraph.iogriddb.netswaydb.simer.au
Technical documentationdocs.bigobject.iodocs.databend.comdgraph.io/­docsdocs.griddb.net
DeveloperBigObject, Inc.Databend LabsDgraph Labs, Inc.Toshiba CorporationSimer Plaha
Initial release20152021201620132018
Current release1.0.59, April 20235.1, August 2022
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustGoC++Scala
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
hosted
Linux
macOS
Linux
OS X
Windows
Linux
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.nonononono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
CLI Client
JDBC
RESTful HTTP API
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Kotlin
Scala
Server-side scripts infoStored proceduresLuanononono
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneyesShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSynchronous replication via RaftSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID at container levelAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
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.yesyesyes
User concepts infoAccess controlnoUsers with fine-grained authorization concept, user rolesno infoPlanned for future releasesAccess rights for users can be defined per databaseno
More information provided by the system vendor
BigObjectDatabendDgraphGridDBSwayDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
BigObjectDatabendDgraphGridDBSwayDB
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