DBMS > HugeGraph vs. NSDb vs. Splunk vs. WakandaDB vs. Weaviate

System Properties Comparison HugeGraph vs. NSDb vs. Splunk vs. WakandaDB vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

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

Analytics Platform for Big Data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

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

Primary database model

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

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	88.71
Rank	#14	Overall
	#2	Search engines

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Score	1.89
Rank	#138	Overall
	#4	Vector DBMS

Website

github.com/hugegraph
hugegraph.apache.org

nsdb.io

www.splunk.com

wakanda.github.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

hugegraph.apache.org/docs

nsdb.io/Architecture

docs.splunk.com/Documentation/Splunk

wakanda.github.io/doc

weaviate.io/developers/weaviate

Developer

Baidu

Splunk Inc.

Wakanda SAS

Weaviate B.V.

Initial release

2018

2017

2003

2012

2019

Current release

0.9

2.7.0 (April 29, 2019), April 2019

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Limited free edition and free developer edition available

Open Source

AGPLv3, extended commercial license 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

Java, Scala

C++, JavaScript

Server operating systems

Linux
macOS
Unix

Linux
macOS

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

also supports composite index and range index

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

SQL-like query language

Splunk Search Processing Language for search commands

GraphQL is used as query language

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

gRPC
HTTP REST
WebSocket

HTTP REST

RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

Groovy
Java
Python

Java
Scala

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

Users, roles and permissions

Access rights for users and roles

yes

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,...
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Competitive advantages

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

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

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

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全面升级！Apache HugeGraph 1.2.0版本发布_apach hugegraph
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18 October 2023, blog.csdn.net

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18 July 2023, Towards Data Science

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