DBMS > Apache Drill vs. FatDB vs. H2 vs. HugeGraph vs. OceanBase

System Properties Comparison Apache Drill vs. FatDB vs. H2 vs. HugeGraph vs. OceanBase

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

A fast-speed and highly-scalable Graph DBMS

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Wide column store

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.66
Rank	#147	Overall
	#68	Relational DBMS

Website

drill.apache.org

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

en.oceanbase.com

Technical documentation

drill.apache.org/docs

www.h2database.com/html/main.html

hugegraph.apache.org/docs

en.oceanbase.com/docs/oceanbase-database

Developer

Apache Software Foundation

FatCloud

Thomas Mueller

Baidu

OceanBase

previously Alibaba and Ant Group

Initial release

2012

2005

2018

2010

Current release

1.20.3, January 2023

2.2.220, July 2023

0.9

4.3.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

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

Open Source

Apache Version 2.0

Open Source

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++

Server operating systems

Linux
OS X
Windows

Windows

All OS with a Java VM

Linux
macOS
Unix

Linux

Data scheme

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Via inetgration in SQL Server

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

C++

Java

Groovy
Java
Python

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

user defined functions

yes

via applications

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

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

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

yes

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

Multi-source replication using Paxos

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

Users, roles and permissions

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

OceanBase Database is the world’s only native distributed database that has set new...
» more

Competitive advantages

High Availability : The five IDCs across three sites disaster recovery solution sets...
» more

Key customers

OceanBase Database has helped over 400 customers across industries upgrade their...
» more

Market metrics

TPC-C No.1 Performance , achieved a result of 707.35 million tpmC in the TPC-C benchmark...
» more

Licensing and pricing models

Mulan PubL v2 license for open source community edition. Commercial license for enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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