DBMS > Alibaba Cloud Table Store vs. AnzoGraph DB vs. Heroic vs. MySQL vs. RocksDB

System Properties Comparison Alibaba Cloud Table Store vs. AnzoGraph DB vs. Heroic vs. MySQL 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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Widely used open source RDBMS

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

Primary database model

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
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	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

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

Website

www.alibabacloud.com/product/table-store

cambridgesemantics.com/anzograph

github.com/spotify/heroic

www.mysql.com

rocksdb.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

spotify.github.io/heroic

dev.mysql.com/doc

github.com/facebook/rocksdb/wiki

Developer

Alibaba

Cambridge Semantics

Spotify

Oracle

since 2010, originally MySQL AB, then Sun

Facebook, Inc.

Initial release

2016

2018

2014

1995

2013

Current release

2.3, January 2021

8.4.0, April 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

with proprietary extensions

APIs and other access methods

HTTP API

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

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

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

Supported programming languages

Java
Python

C++
Java
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication in MPP-Cluster

yes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

ACID

not for MyISAM storage engine

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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