DBMS > Apache IoTDB vs. GeoMesa vs. Lovefield vs. SQLite vs. Valentina Server

System Properties Comparison Apache IoTDB vs. GeoMesa vs. Lovefield vs. SQLite vs. Valentina Server

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

Object-relational database and reports server

Primary database model

Time Series DBMS

Spatial DBMS

Relational DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

iotdb.apache.org

www.geomesa.org

google.github.io/lovefield

www.sqlite.org

www.valentina-db.net

Technical documentation

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

www.geomesa.org/documentation/stable/user/index.html

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

www.sqlite.org/docs.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation

CCRi and others

Google

Dwayne Richard Hipp

Paradigma Software

Initial release

2018

2014

2000

1999

Current release

1.1.0, April 2023

5.0.0, May 2024

2.1.12, February 2017

3.46.0 (23 May 2024), May 2024

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Public Domain

commercial

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

Scala

JavaScript

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

server-less

Linux
OS X
Windows

Data scheme

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
Native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

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

depending on storage layer

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

depending on storage layer

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

depending on storage layer

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 storage layer

yes

using MemoryDB

yes

User concepts

Access control

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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