DBMS > EventStoreDB vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. NCache

System Properties Comparison EventStoreDB vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. NCache

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Fully vectorized database across both GPUs and CPUs

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Microsofts flagship relational DBMS

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

Primary database model

Event Store

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Time Series 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	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

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

Website

www.eventstore.com

www.kinetica.com

azure.microsoft.com/services/synapse-analytics

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

www.alachisoft.com/ncache

Technical documentation

developers.eventstore.com

docs.kinetica.com

docs.microsoft.com/azure/synapse-analytics

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

www.alachisoft.com/resources/docs

Developer

Event Store Limited

Kinetica

Microsoft

Alachisoft

Initial release

2012

2016

1989

2005

Current release

21.2, February 2021

7.1, August 2021

SQL Server 2022, November 2022

5.3.3, April 2024

License

Commercial or Open Source

Open Source

commercial

restricted free version is available

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++

C++

C#, .NET, .NET Core, Java

Server operating systems

Linux
Windows

Linux

hosted

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

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

SQL-like DML and DDL statements

yes

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

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

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

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C#
Java
PHP

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

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

Server-side scripts

Stored procedures

user defined functions

Transact SQL

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

support for stored procedures with SQL-Server CLR

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

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

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

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

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

yes

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

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Market metrics

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Licensing and pricing models

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