DBMS > Alibaba Cloud MaxCompute vs. Bangdb vs. Drizzle vs. H2 vs. KairosDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Bangdb vs. Drizzle vs. H2 vs. KairosDB

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

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

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

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.

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

bangdb.com

www.h2database.com

github.com/kairosdb/kairosdb

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.bangdb.com

www.h2database.com/html/main.html

kairosdb.github.io

Developer

Alibaba

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Thomas Mueller

Initial release

2016

2012

2008

2005

2013

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

2.2.220, July 2023

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

GNU GPL

Open Source

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

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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

hosted

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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-like query language

SQL like support with command line tool

yes

with proprietary extensions

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

Java

C
C#
C++
Java
Python

C
C++
Java
PHP

Java

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Java

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

Implicit feature of the cloud service

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

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

Multi-source replication
Source-replica replication

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

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes, optimistic concurrency control

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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.

yes, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

simple password-based access control

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