DBMS > Graph Engine vs. JaguarDB vs. Oracle NoSQL vs. SAP IQ vs. Snowflake

System Properties Comparison Graph Engine vs. JaguarDB vs. Oracle NoSQL vs. SAP IQ vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Performant, highly scalable DBMS for AI and IoT applications

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Columnar RDBMS optimized for Big Data analytics

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
Key-value store

Key-value store
Vector DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

column-oriented

Relational DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.graphengine.io

www.jaguardb.com

www.oracle.com/database/nosql/technologies/nosql

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

Technical documentation

www.graphengine.io/docs/manual

www.jaguardb.com/support.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

Developer

Microsoft

DataJaguar, Inc.

Oracle

SAP, formerly Sybase

Snowflake Computing Inc.

Initial release

2010

2015

2011

1994

2014

Current release

3.3 July 2023

23.3, December 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

MIT License

Open Source

GPL V3.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

C++

the server part. Clients available in other languages

Java

Server operating systems

.NET

Linux

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
Solaris
Windows

hosted

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

rights management via user accounts

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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