DBMS > IBM Db2 Event Store vs. jBASE vs. Riak TS vs. Sqrrl

System Properties Comparison IBM Db2 Event Store vs. jBASE vs. Riak TS vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

A robust multi-value DBMS comprising development tools and middleware

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Event Store
Time Series DBMS

Multivalue DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

sqrrl.com

Technical documentation

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

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.tiot.jp/riak-docs/riak/ts/latest

Developer

IBM

Rocket Software (formerly Zumasys)

Open Source, formerly Basho Technologies

Amazon

originally Sqrrl Data, Inc.

Initial release

2017

1991

2015

2012

Current release

2.0

5.7

3.0.0, September 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

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++

Erlang

Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

AIX
Linux
Windows

Linux
OS X

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

restricted

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

Embedded SQL for jBASE in BASIC

yes, limited

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP API
Native Erlang Interface

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

.Net
Basic
Jabbascript
Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

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

Access rights can be defined down to the item level

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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