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DBMS > GeoMesa vs. Microsoft Azure Synapse Analytics vs. Milvus vs. TDSQL for MySQL vs. WakandaDB

System Properties Comparison GeoMesa vs. Microsoft Azure Synapse Analytics vs. Milvus vs. TDSQL for MySQL vs. WakandaDB

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelSpatial DBMSRelational DBMSVector DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#214  Overall
#4  Spatial DBMS
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score1.81
Rank#144  Overall
#5  Vector DBMS
Score0.82
Rank#213  Overall
#97  Relational DBMS
Score0.09
Rank#352  Overall
#16  Object oriented DBMS
Websitewww.geomesa.orgazure.microsoft.com/­services/­synapse-analyticsmilvus.iowww.tencentcloud.com/­products/­dcdbwakanda.github.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdwww.tencentcloud.com/­document/­product/­1042wakanda.github.io/­doc
DeveloperCCRi and othersMicrosoftTencentWakanda SAS
Initial release20142016201920132012
Current release4.0.5, February 20242.3.4, January 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache Version 2.0commercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
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 languageScalaC++C++, GoC++, JavaScript
Server operating systemshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
hostedLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesVector, 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.nonononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyesnoyesno
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
PHP
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresnoTransact SQLnoyesyes
Triggersnononoyesyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerSharding, horizontal partitioningShardingAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layeryesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
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 datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layeryesnono
User concepts infoAccess controlyes infodepending on the DBMS used for storageyesRole based access control and fine grained access rightsUsers with fine-grained authorization conceptyes
More information provided by the system vendor
GeoMesaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusTDSQL for MySQLWakandaDB
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
GeoMesaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusTDSQL for MySQLWakandaDB
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