DBMS > Alibaba Cloud Table Store vs. Datomic vs. DolphinDB vs. Ehcache vs. RocksDB

System Properties Comparison Alibaba Cloud Table Store vs. Datomic vs. DolphinDB vs. Ehcache vs. RocksDB

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

A widely adopted Java cache with tiered storage options

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.datomic.com

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

www.ehcache.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Alibaba

Cognitect

DolphinDB, Inc

Terracotta Inc, owned by Software AG

Facebook, Inc.

Initial release

2016

2012

2018

2009

2013

Current release

1.0.6735, June 2023

v2.00.4, January 2022

3.10.0, March 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

free community version available

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

All OS with a Java VM

Linux

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

HTTP API

RESTful HTTP API

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

JCache

C++ API
Java API

Supported programming languages

Java
Python

Clojure
Java

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

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

horizontal partitioning

Sharding

by using Terracotta Server

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

But extensive use of caching in the application peers

yes

by using Terracotta Server

yes

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 (Strong, Eventual, Weak)

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

ACID

yes

supports JTA and can work as an XA resource

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Administrators, Users, Groups

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