DBMS > Brytlyt vs. Microsoft Azure Cosmos DB vs. MySQL vs. TigerGraph vs. Yaacomo

System Properties Comparison Brytlyt vs. Microsoft Azure Cosmos DB vs. MySQL vs. TigerGraph vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Globally distributed, horizontally scalable, multi-model database service

Widely used open source RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key/Value like access via memcached API

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

brytlyt.io

azure.microsoft.com/services/cosmos-db

www.mysql.com

www.tigergraph.com

yaacomo.com

Technical documentation

docs.brytlyt.io

learn.microsoft.com/azure/cosmos-db

dev.mysql.com/doc

docs.tigergraph.com

Developer

Brytlyt

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Q2WEB GmbH

Initial release

2016

2014

1995

2017

2009

Current release

5.0, August 2023

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C, C++ and CUDA

C and C++

C++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

SQL-like query language (GSQL)

yes

APIs and other access methods

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

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

ADO.NET
JDBC
ODBC
Proprietary native API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

JavaScript

yes

proprietary syntax

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

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

not for MyISAM storage engine

yes

Relationships in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

Role-based access control

fine grained access rights according to SQL-standard

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