DBMS > Apache Druid vs. GridDB vs. NuoDB vs. Rockset vs. SQLite

System Properties Comparison Apache Druid vs. GridDB 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

Scalable in-memory time series database optimized for IoT and Big Data

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

Secondary database models

Key-value store
Relational DBMS

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	2.09
Rank	#120	Overall
	#10	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

griddb.net

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

rockset.com

www.sqlite.org

Technical documentation

druid.apache.org/docs/latest/design

docs.griddb.net

doc.nuodb.com

docs.rockset.com

www.sqlite.org/docs.html

Developer

Apache Software Foundation and contributors

Toshiba Corporation

Dassault Systèmes

originally NuoDB, Inc.

Rockset

Dwayne Richard Hipp

Initial release

2012

2013

2019

2000

Current release

29.0.1, April 2024

5.1, August 2022

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also 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++

Server operating systems

Linux
OS X
Unix

Linux

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

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

Read-only SQL queries, including JOINs

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON 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++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.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

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

Source-replica replication

yes

Managed transparently by NuoDB

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

via file-system locks

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

Temporary table

yes

User concepts

Access control

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

Access rights for users can be defined per database

Standard SQL roles/ privileges, Administrative Users

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

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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