DBMS > Hazelcast vs. LevelDB vs. Postgres-XL vs. Yaacomo

System Properties Comparison Hazelcast vs. LevelDB vs. Postgres-XL vs. Yaacomo

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Editorial information provided by DB-Engines

Name

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

Description

A widely adopted in-memory data grid

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Key-value store

Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

hazelcast.com

github.com/google/leveldb

www.postgres-xl.org

yaacomo.com

Technical documentation

hazelcast.org/imdg/docs

github.com/google/leveldb/blob/main/doc/index.md

www.postgres-xl.org/documentation

Developer

Hazelcast

Google

Q2WEB GmbH

Initial release

2008

2011

2014

since 2012, originally named StormDB

2009

Current release

5.3.6, November 2023

1.23, February 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

Open Source

Mozilla public license

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

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux
macOS

Android
Linux
Windows

Data scheme

schema-free

yes

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

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

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 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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

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