DBMS > Apache Impala vs. Atos Standard Common Repository vs. Newts vs. OrigoDB vs. VoltDB

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Newts vs. OrigoDB vs. VoltDB

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Time Series DBMS based on Cassandra

A fully ACID in-memory object graph database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

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	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

impala.apache.org

atos.net/en/convergence-creators/portfolio/standard-common-repository

opennms.github.io/newts

origodb.com

www.voltdb.com

Technical documentation

impala.apache.org/impala-docs.html

github.com/OpenNMS/newts/wiki

origodb.com/docs

docs.voltdb.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

OpenNMS Group

Robert Friberg et al

VoltDB Inc.

Initial release

2013

2016

2014

2009

under the name LiveDB

2010

Current release

4.1.0, June 2022

1703

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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++

Java

Java, C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

Linux
OS X

for development

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

JDBC
ODBC

LDAP

HTTP REST
Java API

.NET Client API
HTTP API
LINQ

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

Java

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

selectable replication factor

based on Cassandra

Source-replica replication

Multi-source replication
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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

depending on model

FOREIGN KEY constraints are not supported

Transaction concepts

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

Atomic execution of specific operations

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Write ahead log

yes

Snapshots and command logging

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

LDAP bind authentication

Role based authorization

Users and roles with access to stored procedures

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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24 June 2022, InfoWorld

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31 August 2021, PR Newswire

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

provided by Google News

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