DBMS > etcd vs. Faircom DB vs. InfluxDB vs. Snowflake vs. UniData,UniVerse

System Properties Comparison etcd vs. Faircom DB vs. InfluxDB vs. Snowflake vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

DBMS for storing time series, events and metrics

Cloud-based data warehousing service for structured and semi-structured data

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	7.64
Rank	#54	Overall
	#5	Key-value stores

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Website

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

www.faircom.com/products/faircom-db

www.influxdata.com/products/influxdb-overview

www.snowflake.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

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

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.influxdata.com/influxdb

docs.snowflake.net/manuals/index.html

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

FairCom Corporation

Snowflake Computing Inc.

Rocket Software

Initial release

1979

2013

2014

1985

Current release

3.4, August 2019

V12, November 2020

2.7.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

MIT-License; commercial enterprise version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
OS X

through Homebrew

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

Numeric data and Strings

yes

optional

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

yes, ANSI SQL with proprietary extensions

SQL-like query language

yes

APIs and other access methods

gRPC
JSON over HTTP

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API
JSON over UDP

CLI Client
JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

JavaScript (Node.js)
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

yes

Triggers

yes, watching key changes

yes

similar concept for controling cloud resources

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

in enterprise version only

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

in enterprise version only

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

simple rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.