DBMS > Brytlyt vs. EsgynDB vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. NuoDB

System Properties Comparison Brytlyt vs. EsgynDB vs. Manticore Search vs. Microsoft Azure Cosmos DB vs. NuoDB

Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

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

Globally distributed, horizontally scalable, multi-model database service

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Relational DBMS

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

brytlyt.io

www.esgyn.cn

manticoresearch.com

azure.microsoft.com/services/cosmos-db

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

docs.brytlyt.io

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

Developer

Brytlyt

Esgyn

Manticore Software

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2016

2015

2017

2014

2013

Current release

5.0, August 2023

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

limited edition free

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, C++ and CUDA

C++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
macOS
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

yes

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

JSON types

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

specific XML-type available, but no XML query functionality.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java Stored Procedures

user defined functions

JavaScript

Java, SQL

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

yes

Managed transparently by NuoDB

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

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