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DBMS > Atos Standard Common Repository vs. HBase vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. HBase vs. Microsoft Azure Synapse Analytics vs. Milvus vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksWide-column store based on Apache Hadoop and on concepts of BigTableElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Wide column storeRelational DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score27.97
Rank#26  Overall
#2  Wide column stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryhbase.apache.orgazure.microsoft.com/­services/­synapse-analyticsmilvus.iospark.apache.org/­sql
Technical documentationhbase.apache.org/­book.htmldocs.microsoft.com/­azure/­synapse-analyticsmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftApache Software Foundation
Initial release20162008201620192014
Current release17032.3.4, January 20212.4.4, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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 languageJavaJavaC++C++, GoScala
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
hostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateoptionaloptions to bring your own types, AVROyesVector, 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.yesnononono
Secondary indexesyesnoyesnono
SQL infoSupport of SQLnonoyesnoSQL-like DML and DDL statements
APIs and other access methodsLDAPJava API
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC
C#
C++
Groovy
Java
PHP
Python
Scala
C#
Java
PHP
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in JavaTransact SQLnono
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual ConsistencyImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonono 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 dataAtomic execution of specific operationsSingle row ACID (across millions of columns)ACIDnono
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.yesyesyesno
User concepts infoAccess controlLDAP bind authenticationAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyesRole based access control and fine grained access rightsno
More information provided by the system vendor
Atos Standard Common RepositoryHBaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQL
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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Atos Standard Common RepositoryHBaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseMilvusSpark SQL
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