DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Transwarp StellarDB vs. Yanza

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. Transwarp StellarDB vs. Yanza

Editorial information provided by DB-Engines
Name	Apache Impala  Xexclude from comparison	Atos Standard Common Repository  Xexclude from comparison	Microsoft Azure AI Search  Xexclude from comparison	Transwarp StellarDB  Xexclude from comparison	Yanza  Xexclude from comparison
		This system has been discontinued and will be removed from the DB-Engines ranking.			Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
Description	Analytic DBMS for Hadoop	Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks	Search-as-a-service for web and mobile app development	A distributed graph DBMS built for enterprise-level graph applications	Time Series DBMS for IoT Applications
Primary database model	Relational DBMS	Document store Key-value store	Search engine	Graph DBMS	Time Series DBMS
Secondary database models	Document store		Vector DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 12.45 Rank #40   Overall #24   Relational DBMS		Score 5.52 Rank #59   Overall #6   Search engines	Score 0.07 Rank #371   Overall #39   Graph DBMS
Website	impala.apache.org	atos.net/en/convergence-creators/portfolio/standard-common-repository	azure.microsoft.com/­en-us/­services/­search	www.transwarp.cn/­en/­product/­stellardb	yanza.com
Technical documentation	impala.apache.org/­impala-docs.html		learn.microsoft.com/­en-us/­azure/­search
Developer	Apache Software Foundation Apache top-level project, originally developed by Cloudera	Atos Convergence Creators	Microsoft	Transwarp	Yanza
Initial release	2013	2016	2015		2015
Current release	4.1.0, June 2022	1703	V1
License Commercial or Open Source	Open Source Apache Version 2	commercial	commercial	commercial	commercial free version available
Cloud-based only Only available as a cloud service	no	no	yes	no	no but mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	C++	Java
Server operating systems	Linux	Linux	hosted		Windows
Data scheme	yes	Schema and schema-less with LDAP views	yes		schema-free
Typing predefined data types such as float or date	yes	optional	yes		no
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	no	yes	no		no
Secondary indexes	yes	yes	yes		no
SQL Support of SQL	SQL-like DML and DDL statements	no	no	SQL-like query language	no
APIs and other access methods	JDBC ODBC	LDAP	RESTful HTTP API	OpenCypher	HTTP API
Supported programming languages	All languages supporting JDBC/ODBC	All languages with LDAP bindings	C# Java JavaScript Python		any language that supports HTTP calls
Server-side scripts Stored procedures	yes user defined functions and integration of map-reduce	no	no		no
Triggers	no	yes	no		yes Timer and event based
Partitioning methods Methods for storing different data on different nodes	Sharding	Sharding cell division	Sharding Implicit feature of the cloud service	horizontal partitioning	none
Replication methods Methods for redundantly storing data on multiple nodes	selectable replication factor	yes	yes Implicit feature of the cloud service		none
MapReduce Offers an API for user-defined Map/Reduce methods	yes query execution via MapReduce		no		no
Consistency concepts Methods to ensure consistency in a distributed system	Eventual Consistency	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency		Immediate Consistency
Foreign keys Referential integrity	no	no	no		no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no	Atomic execution of specific operations	no		no
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	no	yes	no
User concepts Access control	Access rights for users, groups and roles based on Apache Sentry and Kerberos	LDAP bind authentication	yes using Azure authentication	yes	no
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More resources
	Apache Impala	Atos Standard Common Repository	Microsoft Azure AI Search	Transwarp StellarDB	Yanza
Recent citations in the news	Apache Impala becomes Top-Level Project 28 November 2017, SDTimes.com Cloudera Bringing Impala to AWS Cloud 28 November 2017, Datanami Apache Doris just 'graduated': Why care about this SQL data warehouse 24 June 2022, InfoWorld Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop 12 March 2017, Uber Updates & Upserts in Hadoop Ecosystem with Apache Kudu 27 October 2017, KDnuggets provided by Google News		Announcing updates to Azure AI Search to help organizations build and scale generative AI applications 4 April 2024, Microsoft Microsoft and ServiceNow at Knowledge 2024: Introducing generative AI innovation 13 June 2024, Microsoft Azure OpenAI Service: Transforming legal practices with generative AI solutions 12 June 2024, Microsoft Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard) | Azure updates 2 April 2024, Microsoft Raise the bar on AI-powered app development with Azure Database for PostgreSQL 5 June 2024, Microsoft provided by Google News

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