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DBMS > Google Cloud Bigtable vs. HEAVY.AI vs. IBM Cloudant vs. Milvus

System Properties Comparison Google Cloud Bigtable vs. HEAVY.AI vs. IBM Cloudant vs. Milvus

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDatabase as a Service offering based on Apache CouchDBA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelKey-value store
Wide column store
Relational DBMSDocument storeVector DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score2.68
Rank#106  Overall
#20  Document stores
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitecloud.google.com/­bigtablegithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­cloudantmilvus.io
Technical documentationcloud.google.com/­bigtable/­docsdocs.heavy.aicloud.ibm.com/­docs/­Cloudantmilvus.io/­docs/­overview.md
DeveloperGoogleHEAVY.AI, Inc.IBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release2015201620102019
Current release5.10, January 20222.3.4, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
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 languageC++ and CUDAErlangC++, Go
Server operating systemshostedLinuxhostedLinux
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 indexesnonoyesno
SQL infoSupport of SQLnoyesnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Vega
RESTful HTTP/JSON APIRESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoView functions (Map-Reduce) in JavaScriptno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnono infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic lockingyes
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 controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users can be defined per databaseRole based access control and fine grained access rights
More information provided by the system vendor
Google Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM CloudantMilvus
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...
» more
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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More resources
Google Cloud BigtableHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM CloudantMilvus
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