DBMS > LevelDB vs. Pinecone vs. SAP HANA vs. Sequoiadb

System Properties Comparison LevelDB vs. Pinecone vs. SAP HANA vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A managed, cloud-native vector database

In-memory, column based data store. Available as appliance or cloud service

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store

Vector DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

github.com/google/leveldb

www.pinecone.io

www.sap.com/products/hana.html

www.sequoiadb.com

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

docs.pinecone.io/docs/overview

help.sap.com/hana

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Google

Pinecone Systems, Inc

SAP

Sequoiadb Ltd.

Initial release

2011

2019

2010

2013

Current release

1.23, February 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Illumos
Linux
OS X
Windows

hosted

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

yes

oid, date, timestamp, binary, regex

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

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

proprietary protocol using JSON

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

SQLScript, R

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

simple password-based access control

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