DBMS > Apache Druid vs. jBASE vs. Microsoft SQL Server vs. Riak KV vs. Sequoiadb

System Properties Comparison Apache Druid vs. jBASE vs. Microsoft SQL Server vs. Riak KV vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

A robust multi-value DBMS comprising development tools and middleware

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS
Time Series DBMS

Multivalue DBMS

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

druid.apache.org

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

www.microsoft.com/en-us/sql-server

www.sequoiadb.com

Technical documentation

druid.apache.org/docs/latest/design

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

learn.microsoft.com/en-US/sql/sql-server

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

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

Developer

Apache Software Foundation and contributors

Rocket Software (formerly Zumasys)

Microsoft

OpenSource, formerly Basho Technologies

Sequoiadb Ltd.

Initial release

2012

1991

1989

2009

2013

Current release

29.0.1, April 2024

5.7

SQL Server 2022, November 2022

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Erlang

C++

Server operating systems

Linux
OS X
Unix

AIX
Linux
Windows

Linux
Windows

Linux
OS X

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SQL for querying

Embedded SQL for jBASE in BASIC

yes

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

proprietary protocol using JSON

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Basic
Jabbascript
Java

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

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

JavaScript

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

yes, using Riak Security

simple password-based access control

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