DBMS > FatDB vs. RavenDB vs. SAP Adaptive Server vs. Spark SQL vs. Sqrrl

System Properties Comparison FatDB vs. RavenDB vs. SAP Adaptive Server vs. Spark SQL vs. Sqrrl

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Open Source Operational and Transactional Enterprise NoSQL Document Database

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Key-value store

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	3.89
Rank	#90	Overall
	#17	Document stores

Score	44.82
Rank	#25	Overall
	#17	Relational DBMS

Score	23.72
Rank	#35	Overall
	#21	Relational DBMS

Website

ravendb.net

www.sap.com/products/sybase-ase.html

spark.apache.org/sql

sqrrl.com

Technical documentation

ravendb.net/docs

help.sap.com/viewer/product/SAP_ASE

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

Developer

FatCloud

Hibernating Rhinos

SAP, Sybase

Apache Software Foundation

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2010

1987

2014

2012

Current release

5.3, November 2021

16.0

3.3.0, June 2022

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

commercial

Open Source

Apache 2.0

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.

Implementation language

C and C++

Scala

Java

Server operating systems

Windows

Linux
macOS
Raspberry Pi
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
OS X
Windows

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language (RQL)

yes

SQL-like DML and DDL statements

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

.NET Client API
Java Client API
Python Client API
RESTful HTTP API

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

JDBC
ODBC

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
C#
Go
Java
JavaScript (Node.js)
Python
Ruby

C
C++
Cobol
Java
Java
Perl
PHP
Python

Java
Python
R
Scala

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

via applications

yes

Java and Transact-SQL

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes, utilizing Spark Core

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

none

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

MapReduce functions can be defined in Linq

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID, Cluster-wide transaction available

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Can implement custom security layer via applications

Access control on document level using the Authorization Bundle

fine grained access rights according to SQL-standard

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

RavenDB is the pioneer NoSQL Document Database that is fully transactional (ACID)...
» more

Competitive advantages

RavenDB is easy to setup and secure. You can do it in a matter of minutes . Easy...
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Typical application scenarios

IoT for Edge Deployments Fraud Detection Recommendation Engines Product Catalogs...
» more

Key customers

Toyota, Capgemini, Vodafone, Medicaid, Asos, Nomura, RMS Automotive, MSNBC, Pluralsight,...
» more

Market metrics

2 million+ downloads 1000+ customers including Fortune 500 large enterprises
» more

Licensing and pricing models

RavenDB is available on-premise and in the cloud. RavenDB Cloud is available on AWS...
» more

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