DBMS > EXASOL vs. eXtremeDB vs. Google BigQuery vs. Microsoft SQL Server vs. Weaviate

System Properties Comparison EXASOL vs. eXtremeDB vs. Google BigQuery vs. Microsoft SQL Server vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

Large scale data warehouse service with append-only tables

Microsofts flagship relational DBMS

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

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.exasol.com

www.mcobject.com

cloud.google.com/bigquery

www.microsoft.com/en-us/sql-server

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.exasol.com/resources

www.mcobject.com/docs/extremedb.htm

cloud.google.com/bigquery/docs

learn.microsoft.com/en-US/sql/sql-server

weaviate.io/developers/weaviate

Developer

Exasol

McObject

Google

Microsoft

Weaviate B.V.

Initial release

2000

2001

2010

1989

2019

Current release

8.2, 2021

SQL Server 2022, November 2022

1.19, May 2023

License

Commercial or Open Source

commercial

restricted free version is 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

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Implementation language

C and C++

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Linux
Windows

Data scheme

yes

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.

support of XML interfaces available

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

with the option: eXtremeSQL

yes

GraphQL is used as query language

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning / sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes, but depending on the SQL-Server Edition

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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All companies that have data.
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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