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DBMS > Google BigQuery vs. Linter vs. Milvus vs. SurrealDB

System Properties Comparison Google BigQuery vs. Linter vs. Milvus vs. SurrealDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonLinter  Xexclude from comparisonMilvus  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesRDBMS for high security requirementsA DBMS designed for efficient storage of vector data and vector similarity searchesA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSRelational DBMSVector DBMSDocument store
Graph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score52.67
Rank#19  Overall
#13  Relational DBMS
Score0.03
Rank#368  Overall
#156  Relational DBMS
Score3.01
Rank#89  Overall
#4  Vector DBMS
Score1.11
Rank#174  Overall
#30  Document stores
#17  Graph DBMS
Websitecloud.google.com/­bigquerylinter.rumilvus.iosurrealdb.com
Technical documentationcloud.google.com/­bigquery/­docsmilvus.io/­docs/­overview.mdsurrealdb.com/­docs
DeveloperGooglerelex.ruSurrealDB Ltd
Initial release2010199020192022
Current release2.4.4, May 2024v1.5.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source
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 and C++C++, GoRust
Server operating systemshostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
macOS
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and Stringyes
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.nonono
Secondary indexesnoyesno
SQL infoSupport of SQLyesyesnoSQL-like query language
APIs and other access methodsRESTful HTTP/JSON APIADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIGraphQL
RESTful HTTP API
WebSocket
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C++
Go
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACIDnoACID
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.noyes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)fine grained access rights according to SQL-standardRole based access control and fine grained access rightsyes, based on authentication and database rules
More information provided by the system vendor
Google BigQueryLinterMilvusSurrealDB
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 BigQueryLinterMilvusSurrealDB
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