DBMS > Apache Impala vs. Atos Standard Common Repository vs. Cachelot.io vs. Machbase Neo vs. Microsoft Azure AI Search

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Cachelot.io vs. Machbase Neo vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed 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

In-memory caching system

TimeSeries DBMS for AIoT and BigData

Search-as-a-service for web and mobile app development

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store

Time Series DBMS

Search engine

Secondary database models

Document store

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#396	Overall
	#64	Key-value stores

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Score	5.71
Rank	#64	Overall
	#8	Search engines

Website

impala.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

cachelot.io

machbase.com

azure.microsoft.com/en-us/services/search

Technical documentation

impala.apache.org/impala-docs.html

machbase.com/dbms

learn.microsoft.com/en-us/azure/search

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Machbase

Microsoft

Initial release

2013

2016

2015

2013

2015

Current release

4.1.0, June 2022

1703

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Simplified BSD License

commercial

free test version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
macOS
Windows

hosted

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

LDAP

Memcached protocol

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

selectable replication factor

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

simple password-based access control

yes

using Azure authentication

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More resources

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

“Luxembourg is a perfect target area”: Korean accelerator exec
27 October 2022, Delano.lu

provided by Google News

Announcing updates to Azure AI Search to help organizations build and scale generative AI applications
4 April 2024, Microsoft

Public Preview of Azure OpenAI and AI Search in-app connectors for Logic Apps (Standard) | Azure updates
2 April 2024, Microsoft

Microsoft’s Azure AI Search updated with increased storage, vector index size
5 April 2024, InfoWorld

Microsoft Azure AI adds storage power, large RAG app support
5 April 2024, VentureBeat

Microsoft Azure AI Search just got a massive storage increase - here's what you need to know
8 April 2024, ITPro

provided by Google News

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