DBMS > DolphinDB vs. Prometheus vs. Tkrzw vs. Warp 10 vs. Weaviate

System Properties Comparison DolphinDB vs. Prometheus vs. Tkrzw vs. Warp 10 vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Open-source Time Series DBMS and monitoring system

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

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

Primary database model

Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.dolphindb.cn/en/help200/index.html

prometheus.io/docs

www.warp10.io/content/02_Getting_started

weaviate.io/developers/weaviate

Developer

DolphinDB, Inc

Mikio Hirabayashi

SenX

Weaviate B.V.

Initial release

2018

2015

2020

2015

2019

Current release

v2.00.4, January 2022

0.9.3, August 2020

1.19, May 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

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++

Java

Server operating systems

Linux
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

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

SQL

Support of SQL

SQL-like query language

GraphQL is used as query language

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP/JSON API

HTTP API
Jupyter
WebSocket

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++
Java
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

none

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

based on HBase

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

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

using specific database classes

yes

User concepts

Access control

Administrators, Users, Groups

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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

We invite representatives of system vendors to contact us for updating and extending the system information,
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

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

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