DBMS > BoltDB vs. Memcached vs. RocksDB vs. Splunk vs. Weaviate

System Properties Comparison BoltDB vs. Memcached vs. RocksDB vs. Splunk vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

In-memory key-value store, originally intended for caching

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

Analytics Platform for Big Data

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

Primary database model

Key-value store

Search engine

Vector DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

github.com/boltdb/bolt

www.memcached.org

rocksdb.org

www.splunk.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

github.com/memcached/memcached/wiki

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

weaviate.io/developers/weaviate

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Facebook, Inc.

Splunk Inc.

Weaviate B.V.

Initial release

2013

2003

2013

2003

2019

Current release

1.6.25, March 2024

8.11.4, April 2024

1.19, May 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

BSD license

Open Source

BSD

commercial

Limited free edition and free developer edition 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

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux

Linux
OS X
Solaris
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.

yes

Secondary indexes

yes

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

SQL

Support of SQL

Splunk Search Processing Language for search commands

GraphQL is used as query language

APIs and other access methods

Proprietary protocol

C++ API
Java API

HTTP REST

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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

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

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

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...
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Key customers

All companies that have data.
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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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