DBMS > Apache Impala vs. PostGIS vs. RocksDB vs. Trafodion

System Properties Comparison Apache Impala vs. PostGIS vs. RocksDB vs. Trafodion

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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

Spatial extension of PostgreSQL

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Document store

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

impala.apache.org/impala-docs.html

postgis.net/documentation

github.com/facebook/rocksdb/wiki

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Facebook, Inc.

Apache Software Foundation, originally developed by HP

Initial release

2013

2005

2013

2014

Current release

4.1.0, June 2022

3.4.2, February 2024

9.2.1, May 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL v2.0

Open Source

BSD

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

C++, Java

Server operating systems

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

C++ API
Java API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Go
Java
Perl
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on PostgreSQL

yes

yes, via HBase

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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.

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

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