DBMS > Apache Impala vs. Drizzle vs. GeoMesa vs. KairosDB vs. MaxDB

System Properties Comparison Apache Impala vs. Drizzle vs. GeoMesa vs. KairosDB vs. MaxDB

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.

Description

Analytic DBMS for Hadoop

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Distributed Time Series DBMS based on Cassandra or H2

A robust and reliable RDBMS optimized to run all major SAP solutions

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Website

impala.apache.org

www.geomesa.org

github.com/kairosdb/kairosdb

maxdb.sap.com

Technical documentation

impala.apache.org/impala-docs.html

www.geomesa.org/documentation/stable/user/index.html

kairosdb.github.io

maxdb.sap.com/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

CCRi and others

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

2013

2008

2014

2013

1984

Current release

4.1.0, June 2022

7.2.4, September 2012

5.0.0, May 2024

1.2.2, November 2018

7.9.10.12, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

Limited community edition free

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++

Scala

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

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

yes

APIs and other access methods

JDBC
ODBC

JDBC

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

Java
JavaScript

Node.js
PHP
Python

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

depending on storage layer

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

depending on storage layer

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

depending on storage layer

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

depending on the DBMS used for storage

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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6 April 2021, Matthias Gelbmann

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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

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24 June 2022, InfoWorld

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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30 December 2020, AWS Blog

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11 August 2020, SAP News

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21 March 2022, TechTarget

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22 January 2019, IBM

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5 June 2018, Alizila

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