DBMS > Datomic vs. Microsoft SQL Server vs. RocksDB vs. SAP SQL Anywhere vs. ScyllaDB

System Properties Comparison Datomic vs. Microsoft SQL Server vs. RocksDB vs. SAP SQL Anywhere vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Microsofts flagship relational DBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Cassandra and DynamoDB compatible wide column store

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Key-value store

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

www.datomic.com

www.microsoft.com/en-us/sql-server

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

www.scylladb.com

Technical documentation

docs.datomic.com

learn.microsoft.com/en-US/sql/sql-server

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

docs.scylladb.com

Developer

Cognitect

Microsoft

Facebook, Inc.

SAP

formerly Sybase

ScyllaDB

Initial release

2012

1989

2013

1992

2015

Current release

1.0.7075, December 2023

SQL Server 2022, November 2022

9.2.1, May 2024

17, July 2015

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

restricted free version is available

Open Source

BSD

commercial

Open Source

Open Source (AGPL), commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

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.

yes

Secondary indexes

yes

cluster global secondary indices

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol (CQL)

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

Supported programming languages

Clojure
Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, in C/C++, Java, .Net or Perl

yes, Lua

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes, but depending on the SQL-Server Edition

yes

Source-replica replication

Database mirroring

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

yes

ACID

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

in-memory tables

User concepts

Access control

fine grained access rights according to SQL-standard

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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