DBMS > GridGain vs. Pinecone vs. SWC-DB vs. Trafodion

System Properties Comparison GridGain vs. Pinecone vs. SWC-DB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A managed, cloud-native vector database

A high performance, scalable Wide Column DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store
Relational DBMS

Vector DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	3.23
Rank	#92	Overall
	#3	Vector DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.gridgain.com

www.pinecone.io

github.com/kashirin-alex/swc-db
www.swcdb.org

trafodion.apache.org

Technical documentation

www.gridgain.com/docs/index.html

docs.pinecone.io/docs/overview

trafodion.apache.org/documentation.html

Developer

GridGain Systems, Inc.

Pinecone Systems, Inc

Alex Kashirin

Apache Software Foundation, originally developed by HP

Initial release

2007

2019

2020

2014

Current release

GridGain 8.5.1

0.5, April 2021

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL V3

Open Source

Apache 2.0

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, C++, .Net

C++

C++, Java

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP API

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Python

C++

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Java Stored Procedures

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

via user defined functions and HBase

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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