DBMS > Alibaba Cloud Table Store vs. EsgynDB vs. JanusGraph vs. Transwarp StellarDB vs. Weaviate

System Properties Comparison Alibaba Cloud Table Store vs. EsgynDB vs. JanusGraph vs. Transwarp StellarDB vs. Weaviate

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A Graph DBMS optimized for distributed clusters

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

A distributed graph DBMS built for enterprise-level graph applications

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

www.alibabacloud.com/product/table-store

www.esgyn.cn

janusgraph.org

www.transwarp.cn/en/product/stellardb

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.janusgraph.org

weaviate.io/developers/weaviate

Developer

Alibaba

Esgyn

Linux Foundation; originally developed as Titan by Aurelius

Transwarp

Weaviate B.V.

Initial release

2016

2015

2017

2019

Current release

1.0.0, October 2023

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

commercial license available with Weaviate Enterprise

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++, Java

Java

Server operating systems

hosted

Linux

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

yes

SQL-like query language

GraphQL is used as query language

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

OpenCypher

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

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

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

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

User authentification and security via Rexster Graph Server

yes

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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