DBMS > Datomic vs. HEAVY.AI vs. Microsoft SQL Server vs. NCache vs. TinkerGraph

System Properties Comparison Datomic vs. HEAVY.AI vs. Microsoft SQL Server vs. NCache vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Microsofts flagship relational DBMS

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

www.datomic.com

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

www.microsoft.com/en-us/sql-server

www.alachisoft.com/ncache

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.datomic.com

docs.heavy.ai

learn.microsoft.com/en-US/sql/sql-server

www.alachisoft.com/resources/docs

Developer

Cognitect

HEAVY.AI, Inc.

Microsoft

Alachisoft

Initial release

2012

2016

1989

2005

2009

Current release

1.0.7075, December 2023

5.10, January 2022

SQL Server 2022, November 2022

5.3.3, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Enterprise Edition available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++ and CUDA

C++

C#, .NET, .NET Core, Java

Java

Server operating systems

All OS with a Java VM

Linux

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

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

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

IDistributedCache
JCache
LINQ
Proprietary native API

TinkerPop 3

Supported programming languages

Clojure
Java

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Groovy
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

support for stored procedures with SQL-Server CLR

Triggers

By using transaction functions

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Round robin

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

optional

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

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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