DBMS > EJDB vs. HBase vs. LevelDB vs. Ultipa

System Properties Comparison EJDB vs. HBase vs. LevelDB vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

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

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

github.com/Softmotions/ejdb

hbase.apache.org

github.com/google/leveldb

www.ultipa.com

Technical documentation

github.com/Softmotions/ejdb/blob/master/README.md

hbase.apache.org/book.html

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

www.ultipa.com/document

Developer

Softmotions

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Google

Ultipa

Initial release

2012

2008

2011

2019

Current release

2.3.4, January 2021

1.23, February 2021

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache version 2

Open Source

BSD

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

server-less

Linux
Unix
Windows

using Cygwin

Illumos
Linux
OS X
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

options to bring your own types, AVRO

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.

Secondary indexes

SQL

Support of SQL

APIs and other access methods

in-process shared library

Java API
RESTful HTTP API
Thrift

RESTful HTTP API

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Single row ACID (across millions of columns)

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

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