DBMS > EXASOL vs. Google BigQuery vs. SAP IQ vs. SQLite vs. Weaviate

System Properties Comparison EXASOL vs. Google BigQuery vs. SAP IQ vs. SQLite vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Large scale data warehouse service with append-only tables

Columnar RDBMS optimized for Big Data analytics

Widely used embeddable, in-process RDBMS

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

Primary database model

Relational DBMS

column-oriented

Relational DBMS

Vector DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.exasol.com

cloud.google.com/bigquery

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.sqlite.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.exasol.com/resources

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_IQ

www.sqlite.org/docs.html

weaviate.io/developers/weaviate

Developer

Exasol

Google

SAP, formerly Sybase

Dwayne Richard Hipp

Weaviate B.V.

Initial release

2000

2010

1994

2000

2019

Current release

16.1 SPS04, April 2019

3.45.3 (15 April 2024), April 2024

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Public Domain

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

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows

server-less

Data scheme

yes

dynamic column types

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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-92 is not fully supported

GraphQL is used as query language

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

SAP/Sybase Replication Server

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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 for users, groups and roles according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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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