DBMS > Apache Pinot vs. GigaSpaces vs. Newts vs. Riak TS vs. Snowflake

System Properties Comparison Apache Pinot vs. GigaSpaces vs. Newts vs. Riak TS vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Time Series DBMS based on Cassandra

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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Trend Chart

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

pinot.apache.org

www.gigaspaces.com

opennms.github.io/newts

www.snowflake.com

Technical documentation

docs.pinot.apache.org

docs.gigaspaces.com/latest/landing.html

github.com/OpenNMS/newts/wiki

www.tiot.jp/riak-docs/riak/ts/latest

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Gigaspaces Technologies

OpenNMS Group

Open Source, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2015

2000

2014

2015

2014

Current release

1.0.0, September 2023

15.5, September 2020

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Open Source

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

Java, C++, .Net

Java

Erlang

Server operating systems

All OS with a Java JDK11 or higher

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Linux
OS X

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language

SQL-99 for query and DML statements

yes, limited

yes

APIs and other access methods

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP REST
Java API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
Python

.Net
C++
Java
Python
Scala

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Erlang

user defined functions

Triggers

yes, event driven architecture

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

based on Cassandra

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

Role-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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