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DBMS > Databricks vs. Linter vs. Milvus vs. SurrealDB

System Properties Comparison Databricks vs. Linter vs. Milvus vs. SurrealDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLinter  Xexclude from comparisonMilvus  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.RDBMS 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 modelDocument store
Relational DBMS
Relational DBMSVector DBMSDocument store
Graph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  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
Websitewww.databricks.comlinter.rumilvus.iosurrealdb.com
Technical documentationdocs.databricks.commilvus.io/­docs/­overview.mdsurrealdb.com/­docs
DeveloperDatabricksrelex.ruSurrealDB Ltd
Initial release2013199020192022
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 schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesVector, 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.yesnono
Secondary indexesyesyesno
SQL infoSupport of SQLwith Databricks SQLyesnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
RESTful HTTP APIGraphQL
RESTful HTTP API
WebSocket
Supported programming languagesPython
R
Scala
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 and aggregatesyes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
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 controlfine 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
DatabricksLinterMilvusSurrealDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Milvus 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DatabricksLinterMilvusSurrealDB
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