DBMS > Apache Impala vs. atoti vs. IBM Db2 Event Store vs. Sadas Engine

System Properties Comparison Apache Impala vs. atoti vs. IBM Db2 Event Store vs. Sadas Engine

Please select another system to include it in the comparison.

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.

Distributed Event Store optimized for Internet of Things use cases

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Object oriented DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

impala.apache.org

atoti.io

www.ibm.com/products/db2-event-store

www.sadasengine.com

Technical documentation

impala.apache.org/impala-docs.html

docs.atoti.io

www.ibm.com/docs/en/db2-event-store

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ActiveViam

IBM

SADAS s.r.l.

Initial release

2013

2017

2006

Current release

4.1.0, June 2022

2.0

8.0

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free versions available

commercial

free developer edition available

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Multidimensional Expressions (MDX)

yes

through the embedded Spark runtime

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Python

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Active-active shard replication

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

provided by Google News

Best use of cloud: ActiveViam
28 November 2023, Risk.net

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

Share this page