DBMS > Hazelcast vs. JSqlDb vs. Sqrrl vs. WakandaDB vs. YottaDB

System Properties Comparison Hazelcast vs. JSqlDb vs. Sqrrl vs. WakandaDB vs. YottaDB

Editorial information provided by DB-Engines

Name

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

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

JavaScript Query Language Database, stores JavaScript objects and primitives

Adaptable, secure NoSQL built on Apache Accumulo

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

A fast and solid embedded Key-value store

Primary database model

Key-value store

Document store
Object oriented DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS

Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

Relational DBMS

using the Octo plugin

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

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

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

hazelcast.com

jsqldb.org (offline)

sqrrl.com

wakanda.github.io

yottadb.com

Technical documentation

hazelcast.org/imdg/docs

wakanda.github.io/doc

yottadb.com/resources/documentation

Developer

Hazelcast

Konrad von Backstrom

Amazon

originally Sqrrl Data, Inc.

Wakanda SAS

YottaDB, LLC

Initial release

2008

2018

2012

2001

Current release

5.3.6, November 2023

0.8, December 2018

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

commercial

Open Source

AGPLv3, extended commercial license available

Open Source

AGPL 3.0

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++, JavaScript

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

Linux

Linux
OS X
Windows

Docker
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

by using the Octo plugin

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

JavaScript

Actionscript
C

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

JavaScript

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

functions in JavaScript

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

selectable replication factor

making use of Hadoop

none

yes

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

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

Atomic updates per row, document, or graph entity

ACID

optimistic locking

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

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

yes

Users and groups based on OS-security mechanisms

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