DBMS > Pinecone vs. SAP HANA vs. Sqrrl vs. ToroDB

System Properties Comparison Pinecone vs. SAP HANA vs. Sqrrl vs. ToroDB

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A managed, cloud-native vector database

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

Adaptable, secure NoSQL built on Apache Accumulo

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Vector DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store

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	3.02
Rank	#87	Overall
	#3	Vector DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

www.pinecone.io

www.sap.com/products/hana.html

sqrrl.com

github.com/torodb/server

Technical documentation

docs.pinecone.io/docs/overview

help.sap.com/hana

Developer

Pinecone Systems, Inc

SAP

Amazon

originally Sqrrl Data, Inc.

8Kdata

Initial release

2019

2010

2012

2016

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

AGPL-V3

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

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

Implementation language

Java

Server operating systems

hosted

Appliance or cloud-service

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

String, Number, Boolean

yes

string, integer, double, boolean, date, object_id

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

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

making use of Hadoop

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

making use of Hadoop

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic updates per row, document, or graph entity

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

yes

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

Access rights for users and roles

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