DBMS > Alibaba Cloud Table Store vs. Datomic vs. Hive vs. RocksDB

System Properties Comparison Alibaba Cloud Table Store vs. Datomic vs. Hive vs. RocksDB

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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

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Primary database model

Wide column store

Relational DBMS

Key-value store

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

Score	0.24
Rank	#310	Overall
	#12	Wide column stores

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

www.alibabacloud.com/product/table-store

www.datomic.com

hive.apache.org

rocksdb.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.datomic.com

cwiki.apache.org/confluence/display/Hive/Home

github.com/facebook/rocksdb/wiki

Developer

Alibaba

Cognitect

Apache Software Foundation

initially developed by Facebook

Facebook, Inc.

Initial release

2016

2012

2013

Current release

1.0.6735, June 2023

3.1.3, April 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2

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

Java

C++

Server operating systems

hosted

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 DML and DDL statements

APIs and other access methods

HTTP API

RESTful HTTP API

JDBC
ODBC
Thrift

C++ API
Java API

Supported programming languages

Java
Python

Clojure
Java

C++
Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

user defined functions and integration of map-reduce

Triggers

By using transaction functions

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

Sharding

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

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

ACID

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

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

Access rights for users, groups and roles

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