DBMS > IBM Db2 Event Store vs. searchxml vs. TerarkDB

System Properties Comparison IBM Db2 Event Store vs. searchxml vs. TerarkDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

DBMS for structured and unstructured content wrapped with an application server

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Event Store
Time Series DBMS

Native XML DBMS
Search engine

Key-value store

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

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

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

www.searchxml.net/category/products

github.com/bytedance/terarkdb

Technical documentation

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

www.searchxml.net/support/handouts

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

IBM

informationpartners gmbh

ByteDance, originally Terark

Initial release

2017

2015

2016

Current release

2.0

1.0

License

Commercial or Open Source

commercial

free developer edition available

commercial

restricted open source version available

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++

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Windows

Data scheme

yes

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

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

C++ API
Java API

Supported programming languages

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

C++

most other programming languages supported via APIs

C++
Java

Server-side scripts

Stored procedures

yes

on the application server

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

yes

sychronisation to multiple collections

none

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

Transaction concepts

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

multiple readers, single writer

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

Domain, group and role-based access control at the document level and for application services

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Capture and Analyze XXL Data Streams with IBM Db2 Event Store 2.0
22 August 2019, IBM

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

Best cloud databases of 2022
4 October 2022, ITPro

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

provided by Google News

A Chinese company is making the cloud 200x faster · TechNode
3 July 2017, TechNode

provided by Google News

Share this page