DBMS > Heroic vs. LeanXcale vs. Pinecone

System Properties Comparison Heroic vs. LeanXcale vs. Pinecone

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A managed, cloud-native vector database

Primary database model

Time Series DBMS

Key-value store
Relational DBMS

Vector DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Website

github.com/spotify/heroic

www.leanxcale.com

www.pinecone.io

Technical documentation

spotify.github.io/heroic

docs.pinecone.io/docs/overview

Developer

Spotify

LeanXcale

Pinecone Systems, Inc

Initial release

2014

2015

2019

License

Commercial or Open Source

Open Source

Apache 2.0

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

Java

Server operating systems

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

via Elasticsearch

SQL

Support of SQL

yes

through Apache Derby

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

RESTful HTTP API

Supported programming languages

C
Java
Scala

Python

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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