DBMS > Alibaba Cloud Table Store vs. Couchbase vs. HugeGraph vs. JanusGraph

System Properties Comparison Alibaba Cloud Table Store vs. Couchbase vs. HugeGraph vs. JanusGraph

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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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

A fast-speed and highly-scalable Graph DBMS

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Primary database model

Wide column store

Document store

Graph DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Website

www.alibabacloud.com/product/table-store

www.couchbase.com

github.com/hugegraph
hugegraph.apache.org

janusgraph.org

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.couchbase.com

hugegraph.apache.org/docs

docs.janusgraph.org

Developer

Alibaba

Couchbase, Inc.

Baidu

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2016

2011

2018

2017

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

0.9

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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++, Go and Erlang

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Unix

Linux
OS X
Unix
Windows

Data scheme

schema-free

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Java API
RESTful HTTP API
TinkerPop Gremlin

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Groovy
Java
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

asynchronous Gremlin script jobs

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication

including cross data center replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

Access rights based on subaccounts and tokens

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Users, roles and permissions

User authentification and security via Rexster Graph Server

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