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DBMS > Badger vs. BigObject vs. Google Cloud Bigtable vs. Milvus

System Properties Comparison Badger vs. BigObject vs. Google Cloud Bigtable vs. Milvus

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonBigObject  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Analytic DBMS for real-time computations and queriesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value storeRelational DBMS infoa hierachical model (tree) can be imposedKey-value store
Wide column store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#328  Overall
#48  Key-value stores
Score0.13
Rank#329  Overall
#147  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score3.01
Rank#89  Overall
#4  Vector DBMS
Websitegithub.com/­dgraph-io/­badgerbigobject.iocloud.google.com/­bigtablemilvus.io
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.bigobject.iocloud.google.com/­bigtable/­docsmilvus.io/­docs/­overview.md
DeveloperDGraph LabsBigObject, Inc.Google
Initial release2017201520152019
Current release2.4.4, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree community edition availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageGoC++, Go
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)
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesnoVector, Numeric and String
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 indexesnoyesnono
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnono
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP API
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoLuanono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnonenoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic single-row operationsno
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.noyesnoyes
User concepts infoAccess controlnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based access control and fine grained access rights
More information provided by the system vendor
BadgerBigObjectGoogle Cloud BigtableMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
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Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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BadgerBigObjectGoogle Cloud BigtableMilvus
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