DBMS > IBM Db2 Event Store vs. Memcached vs. STSdb vs. Transwarp ArgoDB

System Properties Comparison IBM Db2 Event Store vs. Memcached vs. STSdb vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

In-memory key-value store, originally intended for caching

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Event Store
Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Search engine

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	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

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

www.memcached.org

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/argodb

Technical documentation

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

github.com/memcached/memcached/wiki

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

IBM

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

STS Soft SC

Transwarp

Initial release

2017

2003

2011

Current release

2.0

1.6.25, March 2024

4.0.8, September 2015

License

Commercial or Open Source

commercial

free developer edition available

Open Source

BSD license

Open Source

GPLv2, commercial license available

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++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

FreeBSD
Linux
OS X
Unix
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Proprietary protocol

.NET Client API

Supported programming languages

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

none

Repcached, a Memcached patch, provides this functionallity

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

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

yes

using SASL (Simple Authentication and Security Layer) protocol

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