DBMS > LokiJS vs. Riak TS vs. ScyllaDB vs. Spark SQL

System Properties Comparison LokiJS vs. Riak TS vs. ScyllaDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

In-memory JavaScript DBMS

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

Cassandra and DynamoDB compatible wide column store

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Key-value store

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

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

github.com/techfort/LokiJS

www.scylladb.com

spark.apache.org/sql

Technical documentation

techfort.github.io/LokiJS

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

docs.scylladb.com

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Open Source, formerly Basho Technologies

ScyllaDB

Apache Software Foundation

Initial release

2014

2015

2014

Current release

3.0.0, September 2022

ScyllaDB Open Source 5.4.1, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Open Source (AGPL), commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

JavaScript

Erlang

C++

Scala

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

via views

restricted

yes

cluster global secondary indices

SQL

Support of SQL

yes, limited

SQL-like DML and DDL statements (CQL)

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

HTTP API
Native Erlang Interface

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

JDBC
ODBC

Supported programming languages

JavaScript

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

Erlang

yes, Lua

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Representation of geographical distribution of servers is possible

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

atomic operations within a single collection possible

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

in-memory tables

User concepts

Access control

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
» more

Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more

Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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