DBMS > Memcached vs. Vertica vs. VoltDB vs. Weaviate

System Properties Comparison Memcached vs. Vertica vs. VoltDB vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

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

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Score	1.73
Rank	#143	Overall
	#5	Vector DBMS

Website

www.memcached.org

www.vertica.com

www.voltdb.com

github.com/weaviate/weaviate
weaviate.io

Technical documentation

github.com/memcached/memcached/wiki

vertica.com/documentation

docs.voltdb.com

weaviate.io/developers/weaviate

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

OpenText

previously Micro Focus and Hewlett Packard

VoltDB Inc.

Weaviate B.V.

Initial release

2003

2005

2010

2019

Current release

1.6.25, March 2024

12.0.3, January 2023

11.3, April 2022

1.19, May 2023

License

Commercial or Open Source

Open Source

BSD license

commercial

Limited community edition free

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, C++

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

Linux

Linux
OS X

for development

Data scheme

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

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

SQL

Support of SQL

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes

only a subset of SQL 99

GraphQL is used as query language

APIs and other access methods

Proprietary protocol

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Java API
JDBC
RESTful HTTP/JSON API

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
JavaScript (Node.js)
Perl
PHP
Python
R

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Java

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Users and roles with access to stored procedures

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

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

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

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

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

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

Cost-based models and subscription-based models are both available. One license is...
» more

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

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2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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