DBMS > EsgynDB vs. HyperSQL vs. Manticore Search vs. Snowflake

System Properties Comparison EsgynDB vs. HyperSQL vs. Manticore Search vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.15
Rank	#325	Overall
	#145	Relational DBMS

Score	3.08
Rank	#86	Overall
	#46	Relational DBMS

Score	0.23
Rank	#300	Overall
	#21	Search engines

Score	142.50
Rank	#7	Overall
	#5	Relational DBMS

Website

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

manual.manticoresearch.com

docs.snowflake.net/manuals/index.html

Developer

Esgyn

Manticore Software

Snowflake Computing Inc.

Initial release

2015

2001

2017

2014

Current release

2.7.2, June 2023

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

GPL version 2

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

C++, Java

Java

C++

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

yes

Fixed schema

yes

support of semi-structured data formats (JSON, XML, Avro)

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

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

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

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC
Java

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

Synchronous replication based on Galera library

yes

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

ACID

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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