DBMS > atoti vs. EJDB vs. LeanXcale vs. Ultipa

System Properties Comparison atoti vs. EJDB vs. LeanXcale vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Object oriented DBMS

Document store

Key-value store
Relational DBMS

Graph DBMS

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

atoti.io

github.com/Softmotions/ejdb

www.leanxcale.com

www.ultipa.com

Technical documentation

docs.atoti.io

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

www.ultipa.com/document

Developer

ActiveViam

Softmotions

LeanXcale

Ultipa

Initial release

2012

2015

2019

License

Commercial or Open Source

commercial

free versions available

Open Source

GPLv2

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

Server operating systems

server-less

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Secondary indexes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through Apache Derby

APIs and other access methods

in-process shared library

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

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

C
Java
Scala

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

Server-side scripts

Stored procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Read/Write Locking

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

User concepts

Access control

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More resources

Recent citations in the news

Overview Of Atoti: A Python BI Analytics Tool – AIM
14 May 2021, Analytics India Magazine

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

High-performance computing's role in real-time graph analytics - DataScienceCentral.com
30 January 2024, Data Science Central

provided by Google News

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