DBMS > Alibaba Cloud Table Store vs. HEAVY.AI vs. Heroic vs. Riak KV vs. RocksDB

System Properties Comparison Alibaba Cloud Table Store vs. HEAVY.AI vs. Heroic vs. Riak KV 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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Distributed, fault tolerant key-value store

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

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Key-value store

Secondary database models

Spatial DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.alibabacloud.com/product/table-store

github.com/heavyai/heavydb
www.heavy.ai

github.com/spotify/heroic

rocksdb.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.heavy.ai

spotify.github.io/heroic

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

github.com/facebook/rocksdb/wiki

Developer

Alibaba

HEAVY.AI, Inc.

Spotify

OpenSource, formerly Basho Technologies

Facebook, Inc.

Initial release

2016

2014

2009

2013

Current release

5.10, January 2022

3.2.0, December 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Apache version 2, commercial enterprise edition

Open Source

BSD

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++ and CUDA

Java

Erlang

C++

Server operating systems

hosted

Linux

Linux
OS X

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

via Elasticsearch

restricted

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

JDBC
ODBC
Thrift
Vega

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API
Native Erlang Interface

C++ API
Java API

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC/Thrift
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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Round robin

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

yes

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

Atomic single-row operations

yes

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

yes, using Riak Security

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