DBMS > AllegroGraph vs. Apache IoTDB vs. InfluxDB vs. Lovefield vs. SQLite

System Properties Comparison AllegroGraph vs. Apache IoTDB vs. InfluxDB vs. Lovefield vs. SQLite

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

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

DBMS for storing time series, events and metrics

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

allegrograph.com

iotdb.apache.org

www.influxdata.com/products/influxdb-overview

google.github.io/lovefield

www.sqlite.org

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

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

docs.influxdata.com/influxdb

github.com/google/lovefield/blob/master/docs/spec_index.md

www.sqlite.org/docs.html

Developer

Franz Inc.

Apache Software Foundation

Google

Dwayne Richard Hipp

Initial release

2004

2018

2013

2014

2000

Current release

8.0, December 2023

1.1.0, April 2023

2.7.6, April 2024

2.1.12, February 2017

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Apache 2.0

Open Source

Public Domain

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

Server operating systems

Linux
OS X
Windows

All OS with a Java VM (>= 1.8)

Linux
OS X

through Homebrew

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

tested with Chrome, Firefox, IE, Safari

server-less

Data scheme

yes

RDF schemas

yes

schema-free

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.

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
Native API

HTTP API
JSON over UDP

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

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

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

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

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

selectable replication factor

in enterprise version only

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Strong Consistency with Raft

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

via file-system locks

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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