DBMS > Drizzle vs. Heroic vs. Manticore Search vs. NSDb vs. Weaviate

System Properties Comparison Drizzle vs. Heroic vs. Manticore Search vs. NSDb vs. Weaviate

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Multi-storage database for search, including full-text search.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.48
Rank	#149	Overall
	#8	Vector DBMS

Website

github.com/spotify/heroic

manticoresearch.com

nsdb.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

spotify.github.io/heroic

manual.manticoresearch.com

nsdb.io/Architecture

weaviate.io/developers/weaviate

Developer

Drizzle project, originally started by Brian Aker

Spotify

Manticore Software

Weaviate B.V.

Initial release

2008

2014

2017

2019

Current release

7.2.4, September 2012

6.0, February 2023

1.19, May 2023

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

Apache Version 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

C++

Java, Scala

Server operating systems

FreeBSD
Linux
OS X

FreeBSD
Linux
macOS
Windows

Linux
macOS

Data scheme

yes

schema-free

Fixed schema

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes: int, bigint, decimal, string

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.

Can index from XML

Secondary indexes

yes

via Elasticsearch

yes

full-text index on all search fields

all fields are automatically indexed

yes

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

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

GraphQL is used as query language

APIs and other access methods

JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

gRPC
HTTP REST
WebSocket

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

C
C++
Java
PHP

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Scala

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

Using Apache Lucene

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

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