DBMS > Hazelcast vs. HyperSQL vs. Machbase Neo vs. Microsoft Azure Cosmos DB vs. Sqrrl

System Properties Comparison Hazelcast vs. HyperSQL vs. Machbase Neo vs. Microsoft Azure Cosmos DB vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A widely adopted in-memory data grid

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

TimeSeries DBMS for AIoT and BigData

Globally distributed, horizontally scalable, multi-model database service

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS

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

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

hazelcast.com

hsqldb.org

machbase.com

azure.microsoft.com/services/cosmos-db

sqrrl.com

Technical documentation

hazelcast.org/imdg/docs

hsqldb.org/web/hsqlDocsFrame.html

machbase.com/dbms

learn.microsoft.com/azure/cosmos-db

Developer

Hazelcast

Machbase

Microsoft

Amazon

originally Sqrrl Data, Inc.

Initial release

2008

2001

2013

2014

2012

Current release

5.3.6, November 2023

2.7.2, June 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

based on BSD license

commercial

free test 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

Java

Server operating systems

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS
Windows

hosted

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

All languages supporting JDBC/ODBC
Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Java, SQL

JavaScript

Triggers

yes

Events

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

selectable replication factor

yes

Implicit feature of the cloud service

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

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

Multi-item ACID transactions with snapshot isolation within a partition

Atomic updates per row, document, or graph entity

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

volatile and lookup table

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

simple password-based access control

Access rights can be defined down to the item level

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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