DBMS > Alibaba Cloud Table Store vs. atoti vs. Heroic vs. RocksDB vs. Weaviate

System Properties Comparison Alibaba Cloud Table Store vs. atoti vs. Heroic vs. RocksDB 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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

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

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	0.24
Rank	#310	Overall
	#12	Wide column stores

Score	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	1.89
Rank	#138	Overall
	#4	Vector DBMS

Website

www.alibabacloud.com/product/table-store

atoti.io

github.com/spotify/heroic

rocksdb.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.atoti.io

spotify.github.io/heroic

github.com/facebook/rocksdb/wiki

weaviate.io/developers/weaviate

Developer

Alibaba

ActiveViam

Spotify

Facebook, Inc.

Weaviate B.V.

Initial release

2016

2014

2013

2019

Current release

8.11.4, April 2024

1.19, May 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

BSD

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

Java

C++

Server operating systems

hosted

Linux

Data scheme

schema-free

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

via Elasticsearch

yes

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

GraphQL is used as query language

APIs and other access methods

HTTP API

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

C++ API
Java API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
Python

C
C++
Go
Java
Perl
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

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

yes, multi-version concurrency control (MVCC)

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

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,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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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...
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