DBMS > Lovefield vs. Pinecone vs. Sadas Engine vs. TDSQL for MySQL

System Properties Comparison Lovefield vs. Pinecone vs. Sadas Engine vs. TDSQL for MySQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

A managed, cloud-native vector database

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.96
Rank	#192	Overall
	#88	Relational DBMS

Website

google.github.io/lovefield

www.pinecone.io

www.sadasengine.com

www.tencentcloud.com/products/dcdb

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.pinecone.io/docs/overview

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.tencentcloud.com/document/product/1042

Developer

Google

Pinecone Systems, Inc

SADAS s.r.l.

Tencent

Initial release

2014

2019

2006

2013

Current release

2.1.12, February 2017

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

AIX
Linux
Windows

hosted

Data scheme

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

yes

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

JDBC
ODBC

Supported programming languages

JavaScript

Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

Recent citations in the news

Pinecone serverless goes multicloud as vector database market heats up
27 August 2024, VentureBeat

Using the Pinecone vector database in .NET
12 September 2024, InfoWorld

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

Pinecone launches serverless vector database on Azure, GCP
27 August 2024, TechTarget

Pinecone Makes Accurate, Fast, Scalable Generative AI Accessible to Organizations Large and Small with Launch of its Serverless Vector Database
21 May 2024, PR Newswire

provided by Google News

Tencent Cloud Database recognised for cloud database management systems
21 December 2022, IT Brief Australia

Tencent Cloud partners Allo Bank to boost digital banking in Indonesia
5 July 2023, TechNode Global

Tencent Cloud Distributed Database Ranks First in the Growth Index: Frost & Sullivan's "2021 China Distributed Database Market Report" - PR Newswire APAC
16 May 2022, PR Newswire Asia

Allo Bank stirs up digital banking in Indonesia with Tencent Cloud
20 July 2023, Frontier Enterprise

Indonesia’s Allo Bank taps Tencent Cloud to enhance digital banking services
6 July 2023, FinTech Futures

provided by Google News

Share this page