DBMS > AnzoGraph DB vs. Brytlyt vs. Interbase vs. Microsoft SQL Server vs. SAP Advantage Database Server

System Properties Comparison AnzoGraph DB vs. Brytlyt vs. Interbase vs. Microsoft SQL Server vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Light-weight proven RDBMS

originally from Borland

Microsofts flagship relational DBMS

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

cambridgesemantics.com/anzograph

brytlyt.io

www.embarcadero.com/products/interbase

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

www.sap.com/products/advantage-database-server.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.brytlyt.io

docs.embarcadero.com/products/interbase

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

Developer

Cambridge Semantics

Brytlyt

Embarcadero

Microsoft

Sybase, SAP

Initial release

2018

2016

1984

1989

1993

Current release

2.3, January 2021

5.0, August 2023

InterBase 2020, December 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

free trial version available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++ and CUDA

C++

Server operating systems

Linux

Linux
OS X
Windows

Android
iOS
Linux
OS X
Windows

Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

specific XML-type available, but no XML query functionality.

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
Python

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in PL/pgSQL

yes

Interbase procedure and trigger language

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

Interbase Change Views

yes, but depending on the SQL-Server Edition

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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.

yes

caching of (temporary) tables can be configured

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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