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DBMS > Databricks vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. Milvus

System Properties Comparison Databricks vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. Milvus

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store
Relational DBMS
Document storeRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitewww.databricks.comcloud.google.com/­datastoreazure.microsoft.com/­services/­synapse-analyticsmilvus.io
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.md
DeveloperDatabricksGoogleMicrosoft
Initial release2013200820162019
Current release2.3.4, January 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesyesno
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++C++, Go
Server operating systemshostedhostedhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyes, details hereyesVector, 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.yesnonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)yesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App EngineTransact SQLno
TriggersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
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.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesRole based access control and fine grained access rights
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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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More resources
DatabricksGoogle Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvus
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