DBMS > Pinecone vs. Snowflake vs. TerarkDB vs. WakandaDB

System Properties Comparison Pinecone vs. Snowflake vs. TerarkDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

A managed, cloud-native vector database

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

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

Primary database model

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

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.10
Rank	#356	Overall
	#17	Object oriented DBMS

Website

www.pinecone.io

www.snowflake.com

github.com/bytedance/terarkdb

wakanda.github.io

Technical documentation

docs.pinecone.io/docs/overview

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

wakanda.github.io/doc

Developer

Pinecone Systems, Inc

Snowflake Computing Inc.

ByteDance, originally Terark

Wakanda SAS

Initial release

2019

2014

2016

2012

Current release

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

restricted open source version available

Open Source

AGPLv3, extended commercial license available

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

C++

C++, JavaScript

Server operating systems

hosted

Linux
OS X
Windows

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

CLI Client
JDBC
ODBC

C++ API
Java API

RESTful HTTP API

Supported programming languages

Python

JavaScript (Node.js)
Python

C++
Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

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 with fine-grained authorization concept, user roles and pluggable authentication

yes

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