DBMS > EsgynDB vs. Manticore Search vs. Spark SQL vs. Transwarp StellarDB

System Properties Comparison EsgynDB vs. Manticore Search vs. Spark SQL vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

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

Multi-storage database for search, including full-text search.

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

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

www.esgyn.cn

manticoresearch.com

spark.apache.org/sql

www.transwarp.cn/en/product/stellardb

Technical documentation

manual.manticoresearch.com

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

Developer

Esgyn

Manticore Software

Apache Software Foundation

Transwarp

Initial release

2015

2017

2014

Current release

6.0, February 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

Apache 2.0

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

C++, Java

C++

Scala

Server operating systems

Linux

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC

OpenCypher

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

yes, utilizing Spark Core

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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