DBMS > AlaSQL vs. FeatureBase vs. IBM Db2 Event Store vs. SiriDB

System Properties Comparison AlaSQL vs. FeatureBase vs. IBM Db2 Event Store vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Distributed Event Store optimized for Internet of Things use cases

Open Source Time Series DBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

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

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

alasql.org

www.featurebase.com

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

siridb.com

Technical documentation

github.com/AlaSQL/alasql

docs.featurebase.com

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

docs.siridb.com

Developer

Andrey Gershun & Mathias R. Wulff

Molecula and Pilosa Open Source Contributors

IBM

Cesbit

Initial release

2014

2017

Current release

2022, May 2022

2.0

License

Commercial or Open Source

Open Source

MIT-License

commercial

free developer edition available

Open Source

MIT License

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

JavaScript

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL queries

yes

through the embedded Spark runtime

APIs and other access methods

JavaScript API

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

JavaScript

Java
Python

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

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes, using Linux fsync

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

simple rights management via user accounts

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