DBMS > EsgynDB vs. ScyllaDB vs. Solr vs. SQL.JS vs. Yaacomo

System Properties Comparison EsgynDB vs. ScyllaDB vs. Solr vs. SQL.JS vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Cassandra and DynamoDB compatible wide column store

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

Port of SQLite to JavaScript

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Key-value store

Spatial DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

yaacomo.com

Technical documentation

docs.scylladb.com

solr.apache.org/resources.html

sql.js.org/documentation/index.html

Developer

Esgyn

ScyllaDB

Apache Software Foundation

Alon Zakai

enhancements implemented by others

Q2WEB GmbH

Initial release

2015

2006

2012

2009

Current release

ScyllaDB Open Source 5.4.1, January 2024

9.6.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Open Source (AGPL), commercial license available

Open Source

Apache Version 2

Open Source

commercial

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

C++, Java

C++

Java

JavaScript

Server operating systems

Linux

All OS with a Java VM

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

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

Android
Linux
Windows

Data scheme

yes

schema-free

yes

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

yes

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

yes

cluster global secondary indices

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

Solr Parallel SQL Interface

yes

SQL-92 is not fully supported

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Proprietary protocol (CQL)

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

Java API
RESTful HTTP/JSON API

JavaScript API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

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

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Lua

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

Representation of geographical distribution of servers is possible

yes

none

Source-replica replication

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

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

yes

In-memory capabilities

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

yes

in-memory tables

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

yes

fine grained access rights according to SQL-standard

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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