DBMS > Alibaba Cloud Table Store vs. Microsoft Azure Data Explorer vs. RocksDB vs. Weaviate

System Properties Comparison Alibaba Cloud Table Store vs. Microsoft Azure Data Explorer vs. RocksDB vs. Weaviate

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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

Fully managed big data interactive analytics platform

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

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.alibabacloud.com/product/table-store

azure.microsoft.com/services/data-explorer

rocksdb.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.microsoft.com/en-us/azure/data-explorer

github.com/facebook/rocksdb/wiki

weaviate.io/developers/weaviate

Developer

Alibaba

Microsoft

Facebook, Inc.

Weaviate B.V.

Initial release

2016

2019

2013

2019

Current release

cloud service with continuous releases

9.2.1, May 2024

1.19, May 2023

License

Commercial or Open Source

commercial

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

C++

Server operating systems

hosted

Linux

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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.

yes

Secondary indexes

all fields are automatically indexed

yes

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

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

GraphQL is used as query language

APIs and other access methods

HTTP API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

C++ API
Java API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C
C++
Go
Java
Perl
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

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

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

Azure Active Directory Authentication

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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