DBMS > Apache Phoenix vs. Brytlyt vs. JaguarDB vs. Microsoft Azure Cosmos DB vs. NCache

System Properties Comparison Apache Phoenix vs. Brytlyt vs. JaguarDB vs. Microsoft Azure Cosmos DB vs. NCache

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

Performant, highly scalable DBMS for AI and IoT applications

Globally distributed, horizontally scalable, multi-model database service

Open-Source and Enterprise in-memory Key-Value Store

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Secondary database models

Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.27
Rank	#292	Overall
	#132	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

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

Score	0.91
Rank	#196	Overall
	#29	Key-value stores

Website

phoenix.apache.org

brytlyt.io

www.jaguardb.com

azure.microsoft.com/services/cosmos-db

www.alachisoft.com/ncache

Technical documentation

phoenix.apache.org

docs.brytlyt.io

www.jaguardb.com/support.html

learn.microsoft.com/azure/cosmos-db

www.alachisoft.com/resources/docs

Developer

Apache Software Foundation

Brytlyt

DataJaguar, Inc.

Microsoft

Alachisoft

Initial release

2014

2016

2015

2014

2005

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

5.0, August 2023

3.3 July 2023

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3.0

commercial

Open Source

Enterprise Edition available

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

C++

the server part. Clients available in other languages

C#, .NET, .NET Core, Java

Server operating systems

Linux
Unix
Windows

Linux
OS X
Windows

Linux

hosted

Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

JDBC

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

JDBC
ODBC

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

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

JavaScript

support for stored procedures with SQL-Server CLR

Triggers

yes

JavaScript

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Multi-source replication

yes

Implicit feature of the cloud service

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

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

optimistic locking and pessimistic locking

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

fine grained access rights according to SQL-standard

rights management via user accounts

Access rights can be defined down to the item level

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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