DBMS > HEAVY.AI vs. Ignite vs. Immudb vs. Lovefield vs. SQLite

System Properties Comparison HEAVY.AI vs. Ignite vs. Immudb vs. Lovefield vs. SQLite

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

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

ignite.apache.org

github.com/codenotary/immudb
immudb.io

google.github.io/lovefield

www.sqlite.org

Technical documentation

docs.heavy.ai

apacheignite.readme.io/docs

docs.immudb.io

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

www.sqlite.org/docs.html

Developer

HEAVY.AI, Inc.

Apache Software Foundation

Codenotary

Google

Dwayne Richard Hipp

Initial release

2016

2015

2020

2014

2000

Current release

5.10, January 2022

Apache Ignite 2.6

1.2.3, April 2022

2.1.12, February 2017

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Public Domain

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++, Java, .Net

JavaScript

Server operating systems

Linux

Linux
OS X
Solaris
Windows

BSD
Linux
macOS
Solaris
Windows
z/OS

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

tested with Chrome, Firefox, IE, Safari

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI-99 for query and DML statements, subset of DDL

SQL-like syntax

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
Thrift
Vega

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

gRPC protocol
PostgreSQL wire protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Triggers

yes (cache interceptors and events)

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

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

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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