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DBMS > Datomic vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Teradata Aster

System Properties Comparison Datomic vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Teradata Aster

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  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.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSRelational DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­synapse-analyticsmilvus.io
Technical documentationdocs.datomic.comdocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.md
DeveloperCognitectMicrosoftTeradata
Initial release2012201620192005
Current release1.0.6735, June 20232.3.4, January 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJava, ClojureC++C++, Go
Server operating systemsAll OS with a Java VMhostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Data schemeyesyesFlexible 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 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.nononoyes infoin Aster File Store
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyesnoyes
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
Java
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infoTransaction FunctionsTransact SQLnoR packages
TriggersBy using transaction functionsnonono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding, horizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyesyes 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 methodsnononoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
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 persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnoyesRole based access control and fine grained access rightsfine grained access rights according to SQL-standard
More information provided by the system vendor
DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusTeradata 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
DatomicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusTeradata Aster
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