DBMS > HEAVY.AI vs. LMDB vs. SQLite vs. WakandaDB

System Properties Comparison HEAVY.AI vs. LMDB vs. SQLite vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Widely used embeddable, in-process RDBMS

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

Spatial DBMS

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

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	1.94
Rank	#120	Overall
	#20	Key-value stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

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

www.sqlite.org

wakanda.github.io

Technical documentation

docs.heavy.ai

www.lmdb.tech/doc

www.sqlite.org/docs.html

wakanda.github.io/doc

Developer

HEAVY.AI, Inc.

Symas

Dwayne Richard Hipp

Wakanda SAS

Initial release

2016

2011

2000

2012

Current release

5.10, January 2022

0.9.32, January 2024

3.46.1 (13 August 2024), August 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Public Domain

Open Source

AGPLv3, extended commercial license available

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

C++ and CUDA

C++, JavaScript

Server operating systems

Linux

Linux
Unix
Windows

server-less

Linux
OS X
Windows

Data scheme

yes

schema-free

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

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.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

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

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

via file-system locks

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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