DBMS > Alibaba Cloud Table Store vs. Dragonfly vs. EsgynDB vs. IBM Db2 warehouse

System Properties Comparison Alibaba Cloud Table Store vs. Dragonfly vs. EsgynDB vs. IBM Db2 warehouse

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Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Cloud-based data warehousing service

Primary database model

Wide column store

Key-value store

Relational DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Website

www.alibabacloud.com/product/table-store

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.esgyn.cn

www.ibm.com/products/db2/warehouse

Technical documentation

www.alibabacloud.com/help/en/tablestore

www.dragonflydb.io/docs

Developer

Alibaba

DragonflyDB team and community contributors

Esgyn

IBM

Initial release

2016

2023

2015

2014

Current release

1.0, March 2023

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

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++, Java

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

scheme-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

Java
Python

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

PL/SQL, SQL PL

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

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

Access rights based on subaccounts and tokens

Password-based authentication

fine grained access rights according to SQL-standard

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