DBMS > GeoMesa vs. LevelDB vs. Postgres-XL vs. Valentina Server vs. Weaviate

System Properties Comparison GeoMesa vs. LevelDB vs. Postgres-XL vs. Valentina Server vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Object-relational database and reports server

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

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.52
Rank	#256	Overall
	#117	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Score	1.89
Rank	#138	Overall
	#4	Vector DBMS

Website

www.geomesa.org

github.com/google/leveldb

www.postgres-xl.org

www.valentina-db.net

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.geomesa.org/documentation/stable/user/index.html

github.com/google/leveldb/blob/main/doc/index.md

www.postgres-xl.org/documentation

valentina-db.com/docs/dokuwiki/v5/doku.php

weaviate.io/developers/weaviate

Developer

CCRi and others

Google

Paradigma Software

Weaviate B.V.

Initial release

2014

2011

2014

since 2012, originally named StormDB

1999

2019

Current release

4.0.5, February 2024

1.23, February 2021

10 R1, October 2018

5.7.5

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

BSD

Open Source

Mozilla public license

commercial

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++

Server operating systems

Illumos
Linux
OS X
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

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.

yes

XML type, but no XML query functionality

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
native C library
ODBC
streaming API for large objects

ODBC

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

depending on storage layer

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

depending on storage layer

yes

User concepts

Access control

yes

depending on the DBMS used for storage

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,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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