DBMS > Dgraph vs. Faircom DB vs. ReductStore vs. SAP HANA

System Properties Comparison Dgraph vs. Faircom DB vs. ReductStore vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Graph DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

dgraph.io

www.faircom.com/products/faircom-db

github.com/reductstore
www.reduct.store

www.sap.com/products/hana.html

Technical documentation

dgraph.io/docs

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.reduct.store/docs

help.sap.com/hana

Developer

Dgraph Labs, Inc.

FairCom Corporation

ReductStore LLC

SAP

Initial release

2016

1979

2023

2010

Current release

V12, November 2020

1.9, March 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Restricted, free version available

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

C++, Rust

Server operating systems

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Docker
Linux
macOS
Windows

Appliance or cloud-service

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API

JDBC
ODBC

Supported programming languages

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

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

yes

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

Fine grained access rights according to SQL-standard with additional protections for files

yes

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