DBMS > Apache Drill vs. Bangdb vs. DolphinDB vs. Drizzle vs. H2

System Properties Comparison Apache Drill vs. Bangdb vs. DolphinDB vs. Drizzle vs. H2

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

Converged and high performance database for device data, events, time series, document and graph

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Primary database model

Document store
Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS

Spatial DBMS

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	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

docs.bangdb.com

docs.dolphindb.cn/en/help200/index.html

www.h2database.com/html/main.html

Developer

Apache Software Foundation

Sachin Sinha, BangDB

DolphinDB, Inc

Drizzle project, originally started by Brian Aker

Thomas Mueller

Initial release

2012

2018

2008

2005

Current release

1.20.3, January 2023

BangDB 2.0, October 2021

v2.00.4, January 2022

7.2.4, September 2012

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD 3

commercial

free community version available

Open Source

GNU GPL

Open Source

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

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, C++

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

FreeBSD
Linux
OS X

All OS with a Java VM

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL like support with command line tool

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC

JDBC
ODBC

Supported programming languages

C++

C
C#
C++
Java
Python

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Java
PHP

Java

Server-side scripts

Stored procedures

user defined functions

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Multi-source replication
Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

Depending on the underlying data source

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

User concepts

Access control

Depending on the underlying data source

yes (enterprise version only)

Administrators, Users, Groups

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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