DBMS > BoltDB vs. Hawkular Metrics vs. RocksDB vs. TDengine vs. Weaviate

System Properties Comparison BoltDB vs. Hawkular Metrics vs. RocksDB vs. TDengine vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Time Series DBMS and big data platform

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#5	Vector DBMS

Website

github.com/boltdb/bolt

www.hawkular.org

rocksdb.org

github.com/taosdata/TDengine
tdengine.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

github.com/facebook/rocksdb/wiki

docs.tdengine.com

weaviate.io/developers/weaviate

Developer

Community supported by Red Hat

Facebook, Inc.

TDEngine, previously Taos Data

Weaviate B.V.

Initial release

2013

2014

2013

2019

Current release

9.2.1, May 2024

3.0, August 2022

1.19, May 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

BSD

Open Source

AGPL V3, also commercial editions available

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

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux

Linux
Windows

Data scheme

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.

Secondary indexes

yes

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

SQL

Support of SQL

Standard SQL with extensions for time-series applications

GraphQL is used as query language

APIs and other access methods

HTTP REST

C++ API
Java API

JDBC
RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Go
Java
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

User concepts

Access control

yes

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
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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

TDengine OSS is an open source, cloud native time series database. It includes built-in...
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Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

News

Comprehensive Comparison Between TDengine and MongoDB
6 June 2024

Comprehensive Comparison Between TDengine and TimescaleDB
5 June 2024

Mastering Memory Leak Detection in TDengine
31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

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