DBMS > Hive vs. ScyllaDB vs. SQLite vs. YDB

System Properties Comparison Hive vs. ScyllaDB vs. SQLite vs. YDB

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Cassandra and DynamoDB compatible wide column store

Widely used embeddable, in-process RDBMS

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Document store
Relational DBMS

Secondary database models

Key-value store

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

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

hive.apache.org

www.scylladb.com

www.sqlite.org

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.scylladb.com

www.sqlite.org/docs.html

ydb.tech/en/docs

Developer

Apache Software Foundation

initially developed by Facebook

ScyllaDB

Dwayne Richard Hipp

Yandex

Initial release

2012

2015

2000

2019

Current release

3.1.3, April 2022

ScyllaDB Open Source 5.4.1, January 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Open Source (AGPL), commercial license available

Open Source

Public Domain

Open Source

Apache 2.0; commercial license available

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

Java

C++

Server operating systems

All OS with a Java VM

Linux

server-less

Linux

Data scheme

yes

schema-free

yes

dynamic column types

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

cluster global secondary indices

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like DML and DDL statements (CQL)

yes

SQL-92 is not fully supported

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC
Thrift

Proprietary protocol (CQL)

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

C++
Java
PHP
Python

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

none

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

in-memory tables

yes

User concepts

Access control

Access rights for users, groups and roles

Access rights for users can be defined per object

Access rights defined for Yandex Cloud users

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

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