DBMS > Apache Druid vs. Bangdb vs. Microsoft SQL Server vs. Rockset

System Properties Comparison Apache Druid vs. Bangdb vs. Microsoft SQL Server vs. Rockset

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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

Converged and high performance database for device data, events, time series, document and graph

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

druid.apache.org

bangdb.com

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

rockset.com

Technical documentation

druid.apache.org/docs/latest/design

docs.bangdb.com

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

docs.rockset.com

Developer

Apache Software Foundation and contributors

Sachin Sinha, BangDB

Microsoft

Rockset

Initial release

2012

1989

2019

Current release

29.0.1, April 2024

BangDB 2.0, October 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD 3

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

C++

Server operating systems

Linux
OS X
Unix

Linux

Linux
Windows

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

all fields are automatically indexed

SQL

Support of SQL

SQL for querying

SQL like support with command line tool

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol
RESTful HTTP API

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

HTTP REST

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Java
Python

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

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

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor, Knob for CAP (enterprise version only)

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

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

yes (enterprise version only)

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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