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DBMS > FeatureBase vs. Google Cloud Bigtable vs. HBase vs. Milvus

System Properties Comparison FeatureBase vs. Google Cloud Bigtable vs. HBase vs. Milvus

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Editorial information provided by DB-Engines
NameFeatureBase  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonMilvus  Xexclude from comparison
DescriptionReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Wide-column store based on Apache Hadoop and on concepts of BigTableA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelRelational DBMSKey-value store
Wide column store
Wide column storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websitewww.featurebase.comcloud.google.com/­bigtablehbase.apache.orgmilvus.io
Technical documentationdocs.featurebase.comcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlmilvus.io/­docs/­overview.md
DeveloperMolecula and Pilosa Open Source ContributorsGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2017201520082019
Current release2022, May 20222.3.4, January 20212.3.4, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageGoJavaC++, Go
Server operating systemsLinux
macOS
hostedLinux
Unix
Windows infousing Cygwin
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeyesschema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROVector, 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 indexesnononono
SQL infoSupport of SQLSQL queriesnonono
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
RESTful HTTP API
Supported programming languagesJava
Python
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javano
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesAtomic single-row operationsSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACRole based access control and fine grained access rights
More information provided by the system vendor
FeatureBaseGoogle Cloud BigtableHBaseMilvus
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
FeatureBaseGoogle Cloud BigtableHBaseMilvus
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