DBMS > etcd vs. Hazelcast vs. Microsoft SQL Server vs. Realm vs. UniData,UniVerse

System Properties Comparison etcd vs. Hazelcast vs. Microsoft SQL Server vs. Realm vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

A widely adopted in-memory data grid

Microsofts flagship relational DBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
Spatial DBMS

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

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

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	7.71
Rank	#52	Overall
	#9	Document stores

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Website

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

hazelcast.com

www.microsoft.com/en-us/sql-server

realm.io

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

Technical documentation

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

hazelcast.org/imdg/docs

learn.microsoft.com/en-US/sql/sql-server

realm.io/docs

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

Developer

Hazelcast

Microsoft

Realm, acquired by MongoDB in May 2019

Rocket Software

Initial release

2008

1989

2014

1985

Current release

3.4, August 2019

5.3.6, November 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

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

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

Linux
Windows

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
JSON over HTTP

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes, watching key changes

yes

Events

yes

Change Listeners

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

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

Replicated Map

yes, but depending on the SQL-Server Edition

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

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

In-Memory realm

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

yes

Access rights according to SQL-standard and operating system based

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