DBMS > Linter vs. Lovefield vs. SAP IQ vs. Snowflake vs. Stardog

System Properties Comparison Linter vs. Lovefield vs. SAP IQ vs. Snowflake vs. Stardog

Editorial information provided by DB-Engines

Name

Description

RDBMS for high security requirements

Embeddable relational database for web apps written in pure JavaScript

Columnar RDBMS optimized for Big Data analytics

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

column-oriented

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

linter.ru

google.github.io/lovefield

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

www.snowflake.com

www.stardog.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

docs.stardog.com

Developer

relex.ru

Google

SAP, formerly Sybase

Snowflake Computing Inc.

Stardog-Union

Initial release

1990

2014

1994

2014

2010

Current release

2.1.12, February 2017

16.1 SPS04, April 2019

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C and C++

JavaScript

Java

Server operating systems

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux
macOS
Windows

Data scheme

yes

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

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

JavaScript

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Using read-only observers

yes

similar concept for controling cloud resources

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

SAP/Sybase Replication Server

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Access rights for users and roles

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