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DBMS > Google Cloud Bigtable vs. Milvus vs. SpatiaLite vs. Teradata Aster

System Properties Comparison Google Cloud Bigtable vs. Milvus vs. SpatiaLite vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMilvus  Xexclude from comparisonSpatiaLite  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 searchesSpatial extension of SQLitePlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value store
Wide column store
Vector DBMSSpatial DBMSRelational DBMS
Secondary database modelsRelational 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
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Websitecloud.google.com/­bigtablemilvus.iowww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationcloud.google.com/­bigtable/­docsmilvus.io/­docs/­overview.mdwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperGoogleAlessandro FurieriTeradata
Initial release2015201920082005
Current release2.3.4, January 20245.0.0, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
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++, GoC++
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
server-lessLinux
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.nononoyes infoin Aster File Store
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoyesyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnononoR packages
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes infoSQL Map-Reduce Framework
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
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 rightsnofine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud BigtableMilvusSpatiaLiteTeradata Aster
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 BigtableMilvusSpatiaLiteTeradata Aster
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
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