DBMS > Apache Druid vs. Brytlyt vs. Microsoft Azure Cosmos DB vs. Valentina Server

System Properties Comparison Apache Druid vs. Brytlyt vs. Microsoft Azure Cosmos DB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Globally distributed, horizontally scalable, multi-model database service

Object-relational database and reports server

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

druid.apache.org

brytlyt.io

azure.microsoft.com/services/cosmos-db

www.valentina-db.net

Technical documentation

druid.apache.org/docs/latest/design

docs.brytlyt.io

learn.microsoft.com/azure/cosmos-db

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation and contributors

Brytlyt

Microsoft

Paradigma Software

Initial release

2012

2016

2014

1999

Current release

30.0.0, June 2024

5.0, August 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache license v2

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

Java

C, C++ and CUDA

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL for querying

yes

SQL-like query language

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

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

ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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