DBMS > H2 vs. HarperDB vs. HugeGraph vs. Ignite vs. SQLite

System Properties Comparison H2 vs. HarperDB vs. HugeGraph vs. Ignite vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A fast-speed and highly-scalable Graph DBMS

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.

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store

Graph DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

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

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.h2database.com

www.harperdb.io

github.com/hugegraph
hugegraph.apache.org

ignite.apache.org

www.sqlite.org

Technical documentation

www.h2database.com/html/main.html

docs.harperdb.io/docs

hugegraph.apache.org/docs

apacheignite.readme.io/docs

www.sqlite.org/docs.html

Developer

Thomas Mueller

HarperDB

Baidu

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2005

2017

2018

2015

2000

Current release

2.2.220, July 2023

3.1, August 2021

0.9

Apache Ignite 2.6

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free community edition available

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

Java

Node.js

Java

C++, Java, .Net

Server operating systems

All OS with a Java VM

Linux
OS X

Linux
macOS
Unix

Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

dynamic schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON data types

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like data manipulation statements

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

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
RESTful HTTP API
TinkerPop Gremlin

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Groovy
Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

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

Java Stored Procedures and User-Defined Functions

Custom Functions

since release 3.1

asynchronous Gremlin script jobs

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

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

the nodes on which a table resides can be defined

yes

depending on used storage backend, e.g. Cassandra and HBase

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

yes, using LMDB

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

Access rights for users and roles

Users, roles and permissions

Security Hooks for custom implementations

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