DBMS > Apache Impala vs. EventStoreDB vs. Quasardb vs. Trafodion

System Properties Comparison Apache Impala vs. EventStoreDB vs. Quasardb vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Distributed, high-performance timeseries database

Transactional SQL-on-Hadoop DBMS

Primary database model

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	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

developers.eventstore.com

doc.quasar.ai/master

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Event Store Limited

quasardb

Apache Software Foundation, originally developed by HP

Initial release

2013

2012

2009

2014

Current release

4.1.0, June 2022

21.2, February 2021

3.14.1, January 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache 2.0

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++

C++, Java

Server operating systems

Linux

Linux
Windows

BSD
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication with selectable replication factor

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

yes

via user defined functions and HBase

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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More resources

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