DBMS > Apache IoTDB vs. LMDB vs. Oracle vs. Prometheus vs. WakandaDB

System Properties Comparison Apache IoTDB vs. LMDB vs. Oracle vs. Prometheus vs. WakandaDB

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

A high performant, light-weight, embedded key-value database library

Widely used RDBMS

Open-source Time Series DBMS and monitoring system

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

iotdb.apache.org

www.symas.com/symas-embedded-database-lmdb

www.oracle.com/database

prometheus.io

wakanda.github.io

Technical documentation

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

www.lmdb.tech/doc

docs.oracle.com/en/database

prometheus.io/docs

wakanda.github.io/doc

Developer

Apache Software Foundation

Symas

Oracle

Wakanda SAS

Initial release

2018

2011

1980

2015

2012

Current release

1.1.0, April 2023

0.9.32, January 2024

23c, September 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++, JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Unix
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

yes

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
Native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding, horizontal partitioning

Sharding

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

none

Multi-source replication
Source-replica replication

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes

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