DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Badger vs. BigObject vs. Kinetica vs. Sequoiadb

System Properties Comparison Badger vs. BigObject vs. Kinetica vs. Sequoiadb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigObject  Xexclude from comparisonKinetica  Xexclude from comparisonSequoiadb  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Analytic DBMS for real-time computations and queriesFully vectorized database across both GPUs and CPUsNewSQL database with distributed OLTP and SQL
Primary database modelKey-value storeRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument store
Relational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerbigobject.iowww.kinetica.comwww.sequoiadb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.bigobject.iodocs.kinetica.comwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDGraph LabsBigObject, Inc.KineticaSequoiadb Ltd.
Initial release2017201520122013
Current release7.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree community edition availablecommercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC, C++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes infooid, date, timestamp, binary, regex
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 indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
proprietary protocol using JSON
Supported programming languagesGoC++
Java
JavaScript (Node.js)
Python
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoLuauser defined functionsJavaScript
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnonenoneImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlnonoAccess rights for users and roles on table levelsimple password-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
BadgerBigObjectKineticaSequoiadb
Recent citations in the news

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

Kinetica Delivers Real-Time Vector Similarity Search
22 March 2024, Geospatial World

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here