DBMS > etcd vs. Heroic vs. UniData,UniVerse vs. Valentina Server

System Properties Comparison etcd vs. Heroic vs. UniData,UniVerse vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Object-relational database and reports server

Primary database model

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

Score	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

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

github.com/spotify/heroic

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

www.valentina-db.net

Technical documentation

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

spotify.github.io/heroic

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

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Spotify

Rocket Software

Paradigma Software

Initial release

2014

1985

1999

Current release

3.4, August 2019

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

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

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API

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

ODBC

Supported programming languages

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

.Net
Basic

U2 Basic
C
Java

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes, watching key changes

yes

U2 Basic

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

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 according to SQL-standard and operating system based

fine grained access rights according to SQL-standard

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