DBMS > Apache Druid vs. IBM Db2 Event Store vs. NuoDB vs. Rockset vs. SQLite

System Properties Comparison Apache Druid vs. IBM Db2 Event Store vs. NuoDB vs. Rockset vs. SQLite

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

Distributed Event Store optimized for Internet of Things use cases

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS
Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Relational DBMS
Search engine

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

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

druid.apache.org

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

www.3ds.com/nuodb-distributed-sql-database

rockset.com

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

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

doc.nuodb.com

docs.rockset.com

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

IBM

Dassault Systèmes

originally NuoDB, Inc.

Rockset

Dwayne Richard Hipp

Initial release

2012

2017

2013

2019

2000

Current release

29.0.1, April 2024

2.0

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free developer edition available

commercial

limited edition free

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

C++

Server operating systems

Linux
OS X
Unix

Linux

Linux, macOS, Windows for the developer addition

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

hosted

server-less

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

dynamic typing

yes

not rigid because of 'dynamic typing' concept.

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

yes

through the embedded Spark runtime

yes

Read-only SQL queries, including JOINs

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

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

Go
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Active-active shard replication

yes

Managed transparently by NuoDB

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

MVCC

yes

via file-system locks

Durability

Support for making data persistent

yes

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

Temporary table

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

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

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