DBMS > CouchDB vs. SAP HANA vs. ScyllaDB vs. XTDB

System Properties Comparison CouchDB vs. SAP HANA vs. ScyllaDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

In-memory, column based data store. Available as appliance or cloud service

Cassandra and DynamoDB compatible wide column store

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Key-value store

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

couchdb.apache.org

www.sap.com/products/hana.html

www.scylladb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.couchdb.org/en/stable

help.sap.com/hana

docs.scylladb.com

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

SAP

ScyllaDB

Juxt Ltd.

Initial release

2005

2010

2015

2019

Current release

3.3.3, December 2023

2.0 SPS07 (April 4, 2023), April 2023

ScyllaDB Open Source 5.4.1, January 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Open Source (AGPL), commercial license available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

Erlang

C++

Clojure

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

yes

cluster global secondary indices

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

Proprietary protocol (CQL)

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

HTTP REST
JDBC

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

Clojure
Java

Server-side scripts

Stored procedures

View functions in JavaScript

SQLScript, R

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

selectable replication factor

Representation of geographical distribution of servers is possible

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 database

yes

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...
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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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