DBMS > Galaxybase vs. Ingres vs. Snowflake vs. Solr vs. Weaviate

System Properties Comparison Galaxybase vs. Ingres vs. Snowflake vs. Solr vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

Well established RDBMS

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

A widely used distributed, scalable search engine based on Apache Lucene

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

galaxybase.com

www.actian.com/databases/ingres

www.snowflake.com

solr.apache.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.actian.com/ingres

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

weaviate.io/developers/weaviate

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Actian Corporation

Snowflake Computing Inc.

Apache Software Foundation

Weaviate B.V.

Initial release

2017

1974

originally developed at University Berkely in early 1970s

2014

2006

2019

Current release

Nov 20, November 2021

11.2, May 2022

9.6.1, May 2024

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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 and Java

Java

Server operating systems

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

Strong typed schema

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

All search 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

yes

Solr Parallel SQL Interface

GraphQL is used as query language

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined procedures and functions

yes

user defined functions

Java plugins

Triggers

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

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

Role-based access control

fine grained access rights according to SQL-standard

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

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,...
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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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