DBMS > HEAVY.AI vs. Microsoft Azure Cosmos DB vs. NCache vs. Rockset

System Properties Comparison HEAVY.AI vs. Microsoft Azure Cosmos DB vs. NCache vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Globally distributed, horizontally scalable, multi-model database service

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Document store

Secondary database models

Spatial DBMS

Document store
Search engine

Using distributed Lucene

Relational DBMS
Search engine

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

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

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/cosmos-db

www.alachisoft.com/ncache

rockset.com

Technical documentation

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

www.alachisoft.com/resources/docs

docs.rockset.com

Developer

HEAVY.AI, Inc.

Microsoft

Alachisoft

Rockset

Initial release

2016

2014

2005

2019

Current release

5.10, January 2022

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Enterprise Edition available

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++ and CUDA

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux

hosted

Linux
Windows

hosted

Data scheme

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

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

All properties auto-indexed by default

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

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

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC
Thrift
Vega

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

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

JavaScript

support for stored procedures with SQL-Server CLR

Triggers

JavaScript

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

yes, with selectable consistency level

yes

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

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

Access rights for users and organizations can be defined via Rockset console

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
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