DBMS > Apache IoTDB vs. Netezza vs. PouchDB vs. SQLite vs. TigerGraph

System Properties Comparison Apache IoTDB vs. Netezza vs. PouchDB vs. SQLite vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Data warehouse and analytics appliance part of IBM PureSystems

JavaScript DBMS with an API inspired by CouchDB

Widely used embeddable, in-process RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

iotdb.apache.org

www.ibm.com/products/netezza

pouchdb.com

www.sqlite.org

www.tigergraph.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

pouchdb.com/guides

www.sqlite.org/docs.html

docs.tigergraph.com

Developer

Apache Software Foundation

IBM

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2018

2000

2012

2000

2017

Current release

1.1.0, April 2023

7.1.1, June 2019

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

included in appliance

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Linux

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

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

via views

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

SQL-like query language (GSQL)

APIs and other access methods

JDBC
Native API

JDBC
ODBC
OLE DB

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript

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

C++
Java

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

yes

Users with fine-grained authorization concept

Role-based access control

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