DBMS > Hazelcast vs. HBase vs. JSqlDb vs. Microsoft SQL Server vs. Yaacomo

System Properties Comparison Hazelcast vs. HBase vs. JSqlDb vs. Microsoft SQL Server vs. Yaacomo

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A widely adopted in-memory data grid

Wide-column store based on Apache Hadoop and on concepts of BigTable

JavaScript Query Language Database, stores JavaScript objects and primitives

Microsofts flagship relational DBMS

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

Primary database model

Key-value store

Wide column store

Document store
Object oriented DBMS

Relational DBMS

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	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

hazelcast.com

hbase.apache.org

jsqldb.org (offline)

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

yaacomo.com

Technical documentation

hazelcast.org/imdg/docs

hbase.apache.org/book.html

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

Developer

Hazelcast

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Konrad von Backstrom

Microsoft

Q2WEB GmbH

Initial release

2008

2018

1989

2009

Current release

5.3.6, November 2023

2.3.4, January 2021

0.8, December 2018

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache version 2

Open Source

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

Linux
macOS
Windows

Linux
Windows

Android
Linux
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

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

JCache
JPA
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

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

JDBC
ODBC

Supported programming languages

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

C
C#
C++
Groovy
Java
PHP
Python
Scala

JavaScript

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Coprocessors in Java

functions in JavaScript

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

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
Source-replica replication

none

yes, but depending on the SQL-Server Edition

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency or Eventual Consistency

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Role-based access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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