DBMS > Apache Impala vs. Oracle Coherence vs. RocksDB vs. STSdb vs. ToroDB

System Properties Comparison Apache Impala vs. Oracle Coherence vs. RocksDB vs. STSdb vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for Hadoop

Oracles in-memory data grid solution

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

Relational DBMS

Key-value store

Document store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

impala.apache.org

www.oracle.com/java/coherence

rocksdb.org

github.com/STSSoft/STSdb4

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

docs.oracle.com/en/middleware/standalone/coherence

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Oracle

Facebook, Inc.

STS Soft SC

8Kdata

Initial release

2013

2007

2013

2011

2016

Current release

4.1.0, June 2022

14.1, August 2023

8.11.4, April 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

BSD

Open Source

GPLv2, commercial license available

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

C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux

Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

APIs and other access methods

JDBC
ODBC

JCache
JPA
RESTful HTTP API

C++ API
Java API

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with selectable consistency level

yes

none

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

Access rights for users and roles

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