DBMS > atoti vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. Netezza vs. Transwarp StellarDB

System Properties Comparison atoti vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. Netezza vs. Transwarp StellarDB

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.

Performant, highly scalable DBMS for AI and IoT applications

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Data warehouse and analytics appliance part of IBM PureSystems

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Object oriented DBMS

Key-value store
Vector DBMS

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	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

atoti.io

www.jaguardb.com

azure.microsoft.com/services/synapse-analytics

www.ibm.com/products/netezza

www.transwarp.cn/en/product/stellardb

Technical documentation

docs.atoti.io

www.jaguardb.com/support.html

docs.microsoft.com/azure/synapse-analytics

Developer

ActiveViam

DataJaguar, Inc.

Microsoft

IBM

Transwarp

Initial release

2015

2016

2000

Current release

3.3 July 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

hosted

Linux

included in appliance

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

OpenCypher

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C#
Java
PHP

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Python

Transact SQL

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

rights management via user accounts

yes

Users with fine-grained authorization concept

yes

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