DBMS > Newts vs. Riak TS vs. Snowflake vs. Solr vs. SurrealDB

System Properties Comparison Newts vs. Riak TS vs. Snowflake vs. Solr vs. SurrealDB

Editorial information provided by DB-Engines

Name

Description

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

A widely used distributed, scalable search engine based on Apache Lucene

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Time Series DBMS

Relational DBMS

Search engine

Document store
Graph DBMS

Secondary database models

Spatial DBMS

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

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	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

opennms.github.io/newts

www.snowflake.com

solr.apache.org

surrealdb.com

Technical documentation

github.com/OpenNMS/newts/wiki

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

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

surrealdb.com/docs

Developer

OpenNMS Group

Open Source, formerly Basho Technologies

Snowflake Computing Inc.

Apache Software Foundation

SurrealDB Ltd

Initial release

2014

2015

2014

2006

2022

Current release

3.0.0, September 2022

9.6.0, April 2024

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Open Source

Apache Version 2

Open Source

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

Java

Rust

Server operating systems

Linux
OS X
Windows

Linux
OS X

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
macOS
Windows

Data scheme

schema-free

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes, limited

yes

Solr Parallel SQL Interface

SQL-like query language

APIs and other access methods

HTTP REST
Java API

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Erlang

user defined functions

Java plugins

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Eventual 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

optimistic locking

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

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

yes

yes, based on authentication and database rules

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