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

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

Editorial information provided by DB-Engines

Name

Description

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

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

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.40
Rank	#270	Overall
	#125	Relational 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

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

pinot.apache.org

opennms.github.io/newts

www.snowflake.com

www.tarantool.io

Technical documentation

docs.pinot.apache.org

github.com/OpenNMS/newts/wiki

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

docs.snowflake.net/manuals/index.html

www.tarantool.io/en/doc

Developer

Apache Software Foundation and contributors

OpenNMS Group

Open Source, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2015

2014

2015

2014

2008

Current release

1.0.0, September 2023

3.0.0, September 2022

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

Erlang

C and C++

Server operating systems

All OS with a Java JDK11 or higher

Linux
OS X
Windows

Linux
OS X

hosted

BSD
Linux
macOS

Data scheme

yes

schema-free

yes

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

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

restricted

yes

SQL

Support of SQL

SQL-like query language

yes, limited

yes

Full-featured ANSI SQL support

APIs and other access methods

JDBC

HTTP REST
Java API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Open binary protocol

Supported programming languages

Go
Java
Python

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

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

Erlang

user defined functions

Lua, C and SQL stored procedures

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

yes

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

yes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, full featured in-memory storage engine with persistence

User concepts

Access control

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

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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