DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. AnzoGraph DB vs. CockroachDB vs. Kinetica

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. AnzoGraph DB vs. CockroachDB vs. Kinetica

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Fully vectorized database across both GPUs and CPUs

Primary database model

Wide column store

Document store
Key-value store

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

cambridgesemantics.com/anzograph

www.cockroachlabs.com

www.kinetica.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

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

www.cockroachlabs.com/docs

docs.kinetica.com

Developer

Alibaba

Amazon

Cambridge Semantics

Cockroach Labs

Kinetica

Initial release

2016

2012

2018

2015

2012

Current release

2.3, January 2021

23.1.1, May 2023

7.1, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free trial version available

Open Source

Apache 2.0, commercial license available

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++

Server operating systems

hosted

Linux

Linux
macOS
Windows

Linux

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

dynamic schema

yes

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

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

yes, wire compatible with PostgreSQL

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

RESTful HTTP API

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

JDBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Python

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Automatic sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication in MPP-Cluster

Multi-source replication using RAFT

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency in MPP-Cluster

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

Atomic single-row operations

ACID

ACID across one or more tables within a single AWS account and region

ACID

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

GPU vRAM or System RAM

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users and roles

Role-based access control

Access rights for users and roles on table level

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