DBMS > Apache IoTDB vs. Derby vs. InfluxDB vs. Memgraph vs. SQLite

System Properties Comparison Apache IoTDB vs. Derby vs. InfluxDB vs. Memgraph vs. SQLite

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

DBMS for storing time series, events and metrics

An open source graph database built for real-time streaming and compatible with Neo4j

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	5.30
Rank	#66	Overall
	#36	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	3.00
Rank	#102	Overall
	#8	Graph DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

iotdb.apache.org

db.apache.org/derby

www.influxdata.com/products/influxdb-overview

memgraph.com

www.sqlite.org

Technical documentation

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

db.apache.org/derby/manuals/index.html

docs.influxdata.com/influxdb

memgraph.com/docs

www.sqlite.org/docs.html

Social network pages

Developer

Apache Software Foundation

Memgraph Ltd

Dwayne Richard Hipp

Initial release

2018

1997

2013

2017

2000

Current release

1.1.0, April 2023

10.17.1.0, November 2023

2.7.5, January 2024

3.45.2 (12 March 2024), March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

MIT-License; commercial enterprise version available

commercial

Free license available

Open Source

Public Domain

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 and C++

Server operating systems

All OS with a Java VM (>= 1.8)

All OS with a Java VM

Linux
OS X

through Homebrew

Linux

server-less

Data scheme

yes

schema-free

schema-free and schema-optional

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
Native API

JDBC

HTTP API
JSON over UDP

Bolt protocol
Cypher query language

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Java

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

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 Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

in enterprise version only

Sharding

dynamic graph partitioning

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

selectable replication factor

in enterprise version only

Multi-source replication using RAFT

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

simple rights management via user accounts

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

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Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
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Business Source License ensures a future for the Memgraph community MAGE algorithm...
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Typical application scenarios

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Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
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Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
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Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
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You can check out our pricing model and licenses on the company website .
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