DBMS > Hazelcast vs. Hyprcubd vs. Spark SQL vs. SQL.JS vs. STSdb

System Properties Comparison Hazelcast vs. Hyprcubd vs. Spark SQL vs. SQL.JS vs. STSdb

Editorial information provided by DB-Engines

Name

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

Description

A widely adopted in-memory data grid

Serverless Time Series DBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Port of SQLite to JavaScript

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

hazelcast.com

hyprcubd.com (offline)

spark.apache.org/sql

sql.js.org

github.com/STSSoft/STSdb4

Technical documentation

hazelcast.org/imdg/docs

spark.apache.org/docs/latest/sql-programming-guide.html

sql.js.org/documentation/index.html

Developer

Hazelcast

Hyprcubd, Inc.

Apache Software Foundation

Alon Zakai

enhancements implemented by others

STS Soft SC

Initial release

2008

2014

2012

2011

Current release

5.3.6, November 2023

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

Scala

JavaScript

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC (https)

JDBC
ODBC

JavaScript API

.NET Client API

Supported programming languages

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

Java
Python
R
Scala

JavaScript

C#
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

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

Eventual Consistency

none

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

token access

More information provided by the system vendor

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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