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DBMS > Badger vs. Google Cloud Bigtable vs. GridDB vs. HugeGraph vs. SiriDB

System Properties Comparison Badger vs. Google Cloud Bigtable vs. GridDB vs. HugeGraph vs. SiriDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonSiriDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataA fast-speed and highly-scalable Graph DBMSOpen Source Time Series DBMS
Primary database modelKey-value storeKey-value store
Wide column store
Time Series DBMSGraph DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablegriddb.netgithub.com/­hugegraph
hugegraph.apache.org
siridb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsdocs.griddb.nethugegraph.apache.org/­docsdocs.siridb.com
DeveloperDGraph LabsGoogleToshiba CorporationBaiduCesbit
Initial release20172015201320182017
Current release5.1, August 20220.9
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++JavaC
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
macOS
Unix
Linux
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or datenonoyes infonumerical, string, blob, geometry, boolean, timestampyesyes infoNumeric data
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 indexesnonoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnonoSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Groovy
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnononoasynchronous Gremlin script jobsno
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integritynononoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID at container levelACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseUsers, roles and permissionssimple rights management via user accounts
More information provided by the system vendor
BadgerGoogle Cloud BigtableGridDBHugeGraphSiriDB
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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More resources
BadgerGoogle Cloud BigtableGridDBHugeGraphSiriDB
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