DBMS > Bangdb vs. LevelDB vs. Sequoiadb vs. Weaviate

System Properties Comparison Bangdb vs. LevelDB vs. Sequoiadb vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

NewSQL database with distributed OLTP and SQL

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Document store
Relational DBMS

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

bangdb.com

github.com/google/leveldb

www.sequoiadb.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.bangdb.com

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

www.sequoiadb.com/en/index.php?m=Files&a=index

weaviate.io/developers/weaviate

Developer

Sachin Sinha, BangDB

Google

Sequoiadb Ltd.

Weaviate B.V.

Initial release

2012

2011

2013

2019

Current release

BangDB 2.0, October 2021

1.23, February 2021

1.19, May 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

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

C, C++

C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

Linux

Data scheme

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

oid, date, timestamp, binary, regex

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

secondary, composite, nested, reverse, geospatial

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

GraphQL is used as query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

proprietary protocol using JSON

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C++
Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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.

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

simple password-based access control

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...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

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2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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