DBMS > IBM Db2 Event Store vs. Microsoft SQL Server vs. NuoDB vs. SAP HANA vs. Snowflake

System Properties Comparison IBM Db2 Event Store vs. Microsoft SQL Server vs. NuoDB vs. SAP HANA vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

In-memory, column based data store. Available as appliance or cloud service

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.ibm.com/products/db2-event-store

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

www.3ds.com/nuodb-distributed-sql-database

www.sap.com/products/hana.html

www.snowflake.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

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

doc.nuodb.com

help.sap.com/hana

docs.snowflake.net/manuals/index.html

Developer

IBM

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

SAP

Snowflake Computing Inc.

Initial release

2017

1989

2013

2010

2014

Current release

2.0

SQL Server 2022, November 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted free version is available

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

yes

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Implementation language

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Appliance or cloud-service

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

through the embedded Spark runtime

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

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

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

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

Java, SQL

SQLScript, R

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

data is dynamically stored/cached on the nodes where it is read/written

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

MVCC

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

Temporary table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

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