DBMS > Apache IoTDB vs. Lovefield vs. TerminusDB vs. VelocityDB

System Properties Comparison Apache IoTDB vs. Lovefield vs. TerminusDB vs. VelocityDB

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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

Embeddable relational database for web apps written in pure JavaScript

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
RDF store

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#16	Object oriented DBMS

Website

iotdb.apache.org

google.github.io/lovefield

terminusdb.com

velocitydb.com

Technical documentation

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

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

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

Apache Software Foundation

Google

DataChemist Ltd.

VelocityDB Inc

Initial release

2018

2014

2018

2011

Current release

1.1.0, April 2023

2.1.12, February 2017

11.0.0, January 2023

7.x

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

All OS with a Java VM (>= 1.8)

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

tested with Chrome, Firefox, IE, Safari

Linux

Any that supports .NET

Data scheme

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language (WOQL)

APIs and other access methods

JDBC
Native API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

JavaScript

JavaScript
Python

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

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

none

Graph Partitioning

Sharding

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

none

Journaling Streams

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

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

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

yes

in-memory journaling

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

yes

Role-based access control

Based on Windows Authentication

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