DBMS > IBM Db2 Event Store vs. Sequoiadb vs. Sphinx

System Properties Comparison IBM Db2 Event Store vs. Sequoiadb vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

NewSQL database with distributed OLTP and SQL

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Event Store
Time Series DBMS

Document store
Relational DBMS

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	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

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

www.sequoiadb.com

sphinxsearch.com

Technical documentation

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

www.sequoiadb.com/en/index.php?m=Files&a=index

sphinxsearch.com/docs

Developer

IBM

Sequoiadb Ltd.

Sphinx Technologies Inc.

Initial release

2017

2013

2001

Current release

2.0

3.5.1, February 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Server: AGPL; Client: Apache V2

Open Source

GPL version 2, commercial licence 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

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

full-text index on all search fields

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

proprietary protocol using JSON

Proprietary protocol

Supported programming languages

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

.Net
C++
Java
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

Source-replica replication

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

Document is locked during a transaction

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

The original contents of fields are not stored in the Sphinx index.

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

simple password-based access control

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