DBMS > EsgynDB vs. Postgres-XL vs. Snowflake vs. Speedb vs. Weaviate

System Properties Comparison EsgynDB vs. Postgres-XL vs. Snowflake vs. Speedb vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Cloud-based data warehousing service for structured and semi-structured data

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

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

Primary database model

Relational DBMS

Key-value store

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.20
Rank	#310	Overall
	#44	Key-value stores

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

weaviate.io/developers/weaviate

Developer

Esgyn

Snowflake Computing Inc.

Speedb

Weaviate B.V.

Initial release

2015

2014

since 2012, originally named StormDB

2014

2020

2019

Current release

10 R1, October 2018

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

commercial

Open Source

Apache Version 2.0; commercial license available

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

C++

Server operating systems

Linux

Linux
macOS

hosted

Linux
Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

XML type, but no XML query functionality

yes

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

distributed, parallel query execution

yes

GraphQL is used as query language

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

ACID

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable 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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