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DBMS > BoltDB vs. GridDB vs. Heroic vs. ObjectBox vs. Teradata Aster

System Properties Comparison BoltDB vs. GridDB vs. Heroic vs. ObjectBox vs. Teradata Aster

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonGridDB  Xexclude from comparisonHeroic  Xexclude from comparisonObjectBox  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAn embedded key-value store for Go.Scalable in-memory time series database optimized for IoT and Big DataTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchExtremely fast embedded database for small devices, IoT and MobilePlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeTime Series DBMSTime Series DBMSObject oriented DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#215  Overall
#31  Key-value stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Websitegithub.com/­boltdb/­boltgriddb.netgithub.com/­spotify/­heroicobjectbox.io
Technical documentationdocs.griddb.netspotify.github.io/­heroicdocs.objectbox.io
DeveloperToshiba CorporationSpotifyObjectBox LimitedTeradata
Initial release20132013201420172005
Current release5.1, August 2022
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoApache License 2.0commercial
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 languageGoC++JavaC and C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxAndroid
iOS
Linux
macOS
Windows
Linux
Data schemeschema-freeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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.nonononoyes infoin Aster File Store
Secondary indexesnoyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)nonoyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary native APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGoC
C++
Go
Java
JavaScript (Node.js)
Perl
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++
Java
Python
R
Server-side scripts infoStored proceduresnonononoR packages
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyesonline/offline synchronization between client and serveryes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID at container levelnoACIDACID
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.noyesnonono
User concepts infoAccess controlnoAccess rights for users can be defined per databaseyesfine grained access rights according to SQL-standard
More information provided by the system vendor
BoltDBGridDBHeroicObjectBoxTeradata Aster
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
BoltDBGridDBHeroicObjectBoxTeradata Aster
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