DBMS > Apache Impala vs. Netezza vs. Prometheus vs. RocksDB

System Properties Comparison Apache Impala vs. Netezza vs. Prometheus vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Data warehouse and analytics appliance part of IBM PureSystems

Open-source Time Series DBMS and monitoring system

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

Primary database model

Relational DBMS

Time Series 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	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

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

Website

impala.apache.org

www.ibm.com/products/netezza

prometheus.io

rocksdb.org

Technical documentation

impala.apache.org/impala-docs.html

prometheus.io/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

IBM

Facebook, Inc.

Initial release

2013

2000

2015

2013

Current release

4.1.0, June 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

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

included in appliance

Linux
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

by Federation

yes

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

none

Foreign keys

Referential integrity

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

Users with fine-grained authorization concept

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