DBMS > Apache Impala vs. Drizzle vs. KairosDB vs. ToroDB

System Properties Comparison Apache Impala vs. Drizzle vs. KairosDB vs. ToroDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Distributed Time Series DBMS based on Cassandra or H2

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.71
Rank	#230	Overall
	#20	Time Series DBMS

Website

impala.apache.org

github.com/kairosdb/kairosdb

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

kairosdb.github.io

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

8Kdata

Initial release

2013

2008

2013

2016

Current release

4.1.0, June 2022

7.2.4, September 2012

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

JDBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

In-memory capabilities

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control

Access rights for users and roles

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More resources

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Recent citations in the news

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

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

provided by Google News

Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs
24 May 2019, InfoQ.com

provided by Google News

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