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DBMS > Google Cloud Bigtable vs. Milvus vs. PlanetScale vs. Splunk

System Properties Comparison Google Cloud Bigtable vs. Milvus vs. PlanetScale vs. Splunk

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMilvus  Xexclude from comparisonPlanetScale  Xexclude from comparisonSplunk  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 DBMS designed for efficient storage of vector data and vector similarity searchesScalable, distributed, serverless MySQL database platform built on top of VitessAnalytics Platform for Big Data
Primary database modelKey-value store
Wide column store
Vector DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial 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
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score86.45
Rank#14  Overall
#2  Search engines
Websitecloud.google.com/­bigtablemilvus.ioplanetscale.comwww.splunk.com
Technical documentationcloud.google.com/­bigtable/­docsmilvus.io/­docs/­overview.mdplanetscale.com/­docsdocs.splunk.com/­Documentation/­Splunk
DeveloperGooglePlanetScaleSplunk Inc.
Initial release2015201920202003
Current release2.3.4, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infoLimited free edition and free developer edition available
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++, GoGo
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Docker
Linux
macOS
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoVector, Numeric and Stringyesyes
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.nonoyes
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoyes infowith proprietary extensionsno infoSplunk Search Processing Language for search commands
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
HTTP REST
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonoyes infoproprietary syntaxyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency across shards
Immediate Consistency within a shard
Eventual Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID at shard levelno infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role based access control and fine grained access rightsUsers with fine-grained authorization concept infono user groups or rolesAccess rights for users and roles
More information provided by the system vendor
Google Cloud BigtableMilvusPlanetScaleSplunk
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 BigtableMilvusPlanetScaleSplunk
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