DBMS > EsgynDB vs. Microsoft Azure SQL Database vs. Quasardb vs. STSdb vs. Vertica

System Properties Comparison EsgynDB vs. Microsoft Azure SQL Database vs. Quasardb vs. STSdb vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Database as a Service offering with high compatibility to Microsoft SQL Server

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

www.esgyn.cn

azure.microsoft.com/en-us/products/azure-sql/database

quasar.ai

github.com/STSSoft/STSdb4

www.vertica.com

Technical documentation

docs.microsoft.com/en-us/azure/azure-sql

doc.quasar.ai/master

vertica.com/documentation

Developer

Esgyn

Microsoft

quasardb

STS Soft SC

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

2010

2009

2011

2005

Current release

V12

3.14.1, January 2024

4.0.8, September 2015

12.0.3, January 2023

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, commercial license available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

C++

Server operating systems

Linux

hosted

BSD
Linux
OS X
Windows

Windows

Linux

Data scheme

yes

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

integer and binary

yes

primitive types and user defined types (classes)

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

Secondary indexes

yes

with tags

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

SQL-like query language

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

.NET Client API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes, with always 3 replicas available

Source-replica replication with selectable replication factor

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Bi-directional Spark integration

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

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

show all

Recent citations in the news

Copilot in Azure SQL Database in Private Preview
27 March 2024, InfoQ.com

Microsoft unveils Copilot for Azure SQL Database
27 March 2024, InfoWorld

Azure SQL Database migration to OCI - resources estimation and migration approach
11 January 2024, blogs.oracle.com

Expand the limits of innovation with Azure data
21 March 2024, microsoft.com

Why migrate Windows Server and SQL Server to Azure: ROI, innovation, and free offers
25 April 2024, microsoft.com

provided by Google News

Record quasar is most luminous object in the universe
20 February 2024, EarthSky

Quasar Partners with PTC to Empower IoT Customers with High-Performance Data Solutions
11 September 2023, Datanami

QUASAR yacht (Bilgin, 46.8m, 2016)
3 July 2023, Boat International

Hubble Unexpectedly Finds Double Quasar in Distant Universe
5 April 2023, Science@NASA

Quasar Selected by National Renewable Energy Laboratory to Help with Energy System De-risking and Optimization
6 June 2023, PR Newswire

provided by Google News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

OpenText expands enterprise portfolio with AI and Micro Focus integrations
25 July 2023, VentureBeat

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK | Amazon Web Services
11 February 2021, AWS Blog

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

Vertica by OpenText and Anritsu Sign New Deal for Next-Gen Architecture and 5G Network Capabilities
17 May 2023, PR Newswire

provided by Google News

Share this page