DBMS > EsgynDB vs. IBM Db2 Event Store vs. NuoDB vs. Snowflake vs. Tkrzw

System Properties Comparison EsgynDB vs. IBM Db2 Event Store vs. NuoDB vs. Snowflake vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Distributed Event Store optimized for Internet of Things use cases

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

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Key-value store

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.esgyn.cn

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

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

www.snowflake.com

dbmx.net/tkrzw

Technical documentation

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

doc.nuodb.com

docs.snowflake.net/manuals/index.html

Developer

Esgyn

IBM

Dassault Systèmes

originally NuoDB, Inc.

Snowflake Computing Inc.

Mikio Hirabayashi

Initial release

2015

2017

2013

2014

2020

Current release

2.0

0.9.3, August 2020

License

Commercial or Open Source

commercial

free developer edition available

commercial

limited edition free

commercial

Open Source

Apache Version 2.0

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++, Java

C and C++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

hosted

Linux
macOS

Data scheme

yes

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

schema-free

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
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

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

JavaScript (Node.js)
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Java, SQL

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Active-active shard replication

yes

Managed transparently by NuoDB

yes

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

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

yes

No - written data is immutable

yes

MVCC

yes

Durability

Support for making data persistent

yes

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

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

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