DBMS > Apache Impala vs. Trafodion vs. Vitess

System Properties Comparison Apache Impala vs. Trafodion vs. Vitess

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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

Transactional SQL-on-Hadoop DBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	12.57
Rank	#40	Overall
	#24	Relational DBMS

Score	0.83
Rank	#205	Overall
	#95	Relational DBMS

Website

impala.apache.org

trafodion.apache.org

vitess.io

Technical documentation

impala.apache.org/impala-docs.html

trafodion.apache.org/documentation.html

vitess.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation, originally developed by HP

The Linux Foundation, PlanetScale

Initial release

2013

2014

2013

Current release

4.1.0, June 2022

2.3.0, February 2019

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache Version 2.0, commercial licenses 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++

C++, Java

Server operating systems

Linux

Docker
Linux
macOS

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

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

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

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, via HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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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

Tabular, the vendor-neutral data store based on Apache Iceberg, raises $26M in funding
19 September 2023, SiliconANGLE News

Apache Iceberg Changes Everything: What's Underneath?
28 August 2023, Spiceworks News and Insights

Introduction to Bigdata and Hadoop Ecosystem | by Arpita Mishra | Jun, 2024
7 June 2024, Medium

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

An Open Source Tour de Force at Apache: Big Data 2016
11 May 2016, Datanami

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

PlanetScale offers undo button to reverse schema migration without losing data
24 March 2022, The Register

PlanetScale Announces $50M in Series C Funding to Accelerate Development and Adoption of Infinitely Scalable Serverless MySQL Database
16 November 2021, Business Wire

provided by Google News

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