DBMS > EsgynDB vs. Quasardb vs. Spark SQL vs. ToroDB

System Properties Comparison EsgynDB vs. Quasardb vs. Spark SQL vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Distributed, high-performance timeseries database

Spark SQL is a component on top of 'Spark Core' for structured data processing

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.esgyn.cn

quasar.ai

spark.apache.org/sql

github.com/torodb/server

Technical documentation

doc.quasar.ai/master

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Esgyn

quasardb

Apache Software Foundation

8Kdata

Initial release

2015

2009

2014

2016

Current release

3.14.1, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

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

Open Source

Apache 2.0

Open Source

AGPL-V3

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

C++, Java

C++

Scala

Java

Server operating systems

Linux

BSD
Linux
OS X
Windows

Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

yes

string, integer, double, boolean, date, object_id

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

with tags

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication with selectable replication factor

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

Access rights for users and roles

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