DBMS > Hazelcast vs. Pinecone vs. Transwarp Hippo

System Properties Comparison Hazelcast vs. Pinecone vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

A managed, cloud-native vector database

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Key-value store

Vector DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	5.47
Rank	#58	Overall
	#6	Key-value stores

Score	3.17
Rank	#81	Overall
	#5	Vector DBMS

Score	0.01
Rank	#383	Overall
	#21	Vector DBMS

Website

hazelcast.com

www.pinecone.io

www.transwarp.cn/en/subproduct/hippo

Technical documentation

hazelcast.org/imdg/docs

docs.pinecone.io/docs/overview

Developer

Hazelcast

Pinecone Systems, Inc

Initial release

2008

2019

2023

Current release

5.3.6, November 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

hosted

Linux
macOS

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

String, Number, Boolean

Vector, Numeric and String

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

RESTful HTTP API

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Python

C++
Java
Python

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

Role based access control and fine grained access rights

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