DBMS > HEAVY.AI vs. Infobright vs. LevelDB vs. Lovefield

System Properties Comparison HEAVY.AI vs. Infobright vs. LevelDB vs. Lovefield

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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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

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

ignitetech.com/softwarelibrary/infobrightdb

github.com/google/leveldb

google.github.io/lovefield

Technical documentation

docs.heavy.ai

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

HEAVY.AI, Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Google

Initial release

2016

2005

2011

2014

Current release

5.10, January 2022

1.23, February 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

BSD

Open Source

Apache 2.0

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
Windows

Illumos
Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

Server-side scripts

Stored procedures

Triggers

Using read-only observers

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

Source-replica 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

Durability

Support for making data persistent

yes

with automatic compression on writes

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

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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