DBMS > etcd vs. Graphite vs. Infobright vs. Sadas Engine

System Properties Comparison etcd vs. Graphite vs. Infobright vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

github.com/graphite-project/graphite-web

ignitetech.com/softwarelibrary/infobrightdb

www.sadasengine.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

graphite.readthedocs.io

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Chris Davis

Ignite Technologies Inc.; formerly InfoBright Inc.

SADAS s.r.l.

Initial release

2006

2005

2006

Current release

3.4, August 2019

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

free trial version available

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

Python

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
Unix

Linux
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

HTTP API
Sockets

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

JavaScript (Node.js)
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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