DBMS > Apache Impala vs. atoti vs. Microsoft Azure Cosmos DB vs. OceanBase

System Properties Comparison Apache Impala vs. atoti vs. Microsoft Azure Cosmos DB vs. OceanBase

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Globally distributed, horizontally scalable, multi-model database service

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Relational DBMS

Object oriented DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store

Spatial DBMS

Document store
Wide column store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.66
Rank	#147	Overall
	#68	Relational DBMS

Website

impala.apache.org

atoti.io

azure.microsoft.com/services/cosmos-db

en.oceanbase.com

Technical documentation

impala.apache.org/impala-docs.html

docs.atoti.io

learn.microsoft.com/azure/cosmos-db

en.oceanbase.com/docs/oceanbase-database

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ActiveViam

Microsoft

OceanBase

previously Alibaba and Ant Group

Initial release

2013

2014

2010

Current release

4.1.0, June 2022

4.3.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free versions available

commercial

Open Source

Commercial license available

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

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Multidimensional Expressions (MDX)

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Python

JavaScript

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Implicit feature of the cloud service

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

OceanBase Database is the world’s only native distributed database that has set new...
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Competitive advantages

High Availability : The five IDCs across three sites disaster recovery solution sets...
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Key customers

OceanBase Database has helped over 400 customers across industries upgrade their...
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Market metrics

TPC-C No.1 Performance , achieved a result of 707.35 million tpmC in the TPC-C benchmark...
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Licensing and pricing models

Mulan PubL v2 license for open source community edition. Commercial license for enterprise...
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