DBMS > Alibaba Cloud Table Store vs. Bangdb vs. Riak TS vs. Yaacomo

System Properties Comparison Alibaba Cloud Table Store vs. Bangdb vs. Riak TS vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Wide column store

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

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

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

bangdb.com

yaacomo.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.bangdb.com

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Alibaba

Sachin Sinha, BangDB

Open Source, formerly Basho Technologies

Q2WEB GmbH

Initial release

2016

2012

2015

2009

Current release

BangDB 2.0, October 2021

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Erlang

Server operating systems

hosted

Linux

Linux
OS X

Android
Linux
Windows

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

restricted

yes

SQL

Support of SQL

SQL like support with command line tool

yes, limited

yes

APIs and other access methods

HTTP API

Proprietary protocol
RESTful HTTP API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

Java
Python

C
C#
C++
Java
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

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

horizontal partitioning

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)

selectable replication factor

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

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 based on subaccounts and tokens

yes (enterprise version only)

fine grained access rights according to SQL-standard

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