DBMS > Apache Druid vs. Kinetica vs. NSDb vs. TimesTen vs. ToroDB

System Properties Comparison Apache Druid vs. Kinetica vs. NSDb vs. TimesTen vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Fully vectorized database across both GPUs and CPUs

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

In-Memory RDBMS compatible to Oracle

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS
Time Series DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

druid.apache.org

www.kinetica.com

nsdb.io

www.oracle.com/database/technologies/related/timesten.html

github.com/torodb/server

Technical documentation

druid.apache.org/docs/latest/design

docs.kinetica.com

nsdb.io/Architecture

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation and contributors

Kinetica

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

8Kdata

Initial release

2012

2017

1998

2016

Current release

29.0.1, April 2024

7.1, August 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache Version 2.0

commercial

Open Source

AGPL-V3

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

Java

C, C++

Java, Scala

Java

Server operating systems

Linux
OS X
Unix

Linux

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

All OS with a Java 7 VM

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

Java
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

PL/SQL

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate 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

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

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 and roles on table level

fine grained access rights according to SQL-standard

Access rights for users and roles

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