DBMS > IBM Db2 Event Store vs. Newts vs. SQream DB vs. TimesTen

System Properties Comparison IBM Db2 Event Store vs. Newts vs. SQream DB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Time Series DBMS based on Cassandra

a GPU-based, columnar RDBMS for big data analytics workloads

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Event Store
Time Series DBMS

Time Series DBMS

Relational DBMS

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

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

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

opennms.github.io/newts

sqream.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

github.com/OpenNMS/newts/wiki

docs.sqream.com

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

IBM

OpenNMS Group

SQream Technologies

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

2014

2017

1998

Current release

2.0

2022.1.6, December 2022

Release 22.1

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Linux

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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.

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

HTTP REST
Java API

.Net
JDBC
ODBC

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

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

Java

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

user defined functions in Python

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

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

by means of logfiles and checkpoints

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

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