DBMS > Apache Impala vs. Atos Standard Common Repository vs. Blueflood vs. Yaacomo vs. YottaDB

System Properties Comparison Apache Impala vs. Atos Standard Common Repository vs. Blueflood vs. Yaacomo vs. YottaDB

Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is 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

Scalable TimeSeries DBMS based on Cassandra

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

Relational DBMS

using the Octo plugin

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

impala.apache.org

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

blueflood.io

yaacomo.com

yottadb.com

Technical documentation

impala.apache.org/impala-docs.html

github.com/rax-maas/blueflood/wiki

yottadb.com/resources/documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Atos Convergence Creators

Rackspace

Q2WEB GmbH

YottaDB, LLC

Initial release

2013

2016

2013

2009

2001

Current release

4.1.0, June 2022

1703

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0

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

Server operating systems

Linux

Linux
OS X

Android
Linux
Windows

Docker
Linux

Data scheme

yes

Schema and schema-less with LDAP views

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

by using the Octo plugin

APIs and other access methods

JDBC
ODBC

LDAP

HTTP REST

JDBC
ODBC

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

selectable replication factor

based on Cassandra

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 or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

optimistic locking

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

LDAP bind authentication

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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More resources

Recent citations in the news

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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