DBMS > Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. PlanetScale vs. SAP HANA

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Microsoft Azure AI Search vs. PlanetScale vs. SAP HANA

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

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

Scalable, distributed, serverless MySQL database platform built on top of Vitess

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS

Document store
Key-value store

Search engine

Relational DBMS

Secondary database models

Document store

Vector DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

impala.apache.org

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

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

planetscale.com

www.sap.com/products/hana.html

Technical documentation

impala.apache.org/impala-docs.html

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

planetscale.com/docs

help.sap.com/hana

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Microsoft

PlanetScale

SAP

Initial release

2013

2016

2015

2020

2010

Current release

4.1.0, June 2022

1703

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

hosted

Docker
Linux
macOS

Appliance or cloud-service

Data scheme

yes

Schema and schema-less with LDAP views

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

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

LDAP

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C#
Java
JavaScript
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Implicit feature of the cloud service

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

yes

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

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic execution of specific operations

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

LDAP bind authentication

yes

using Azure authentication

Users with fine-grained authorization concept

no user groups or roles

yes

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