DBMS > Apache Impala vs. Drizzle vs. MaxDB vs. RocksDB

System Properties Comparison Apache Impala vs. Drizzle vs. MaxDB vs. RocksDB

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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.

Description

Analytic DBMS for Hadoop

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

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Key-value store

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	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

impala.apache.org

maxdb.sap.com

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

maxdb.sap.com/documentation

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

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

Facebook, Inc.

Initial release

2013

2008

1984

2013

Current release

4.1.0, June 2022

7.2.4, September 2012

7.9.10.12, February 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GNU GPL

commercial

Limited community edition free

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

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

ADO.NET
JDBC
ODBC
WebDAV

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C#
Java
Perl
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

yes

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

ACID

yes

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.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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