DBMS > atoti vs. LeanXcale vs. Transwarp StellarDB vs. Ultipa

System Properties Comparison atoti vs. LeanXcale vs. Transwarp StellarDB 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.

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

A distributed graph DBMS built for enterprise-level graph applications

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Object oriented DBMS

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

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

atoti.io

www.leanxcale.com

www.transwarp.cn/en/product/stellardb

www.ultipa.com

Technical documentation

docs.atoti.io

www.ultipa.com/document

Developer

ActiveViam

LeanXcale

Transwarp

Ultipa

Initial release

2015

2019

License

Commercial or Open Source

commercial

free versions available

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

Data scheme

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through Apache Derby

SQL-like query language

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

OpenCypher

RESTful HTTP API

Supported programming languages

C
Java
Scala

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

Server-side scripts

Stored procedures

Python

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

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

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

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

yes

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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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