DBMS > Faircom DB vs. Heroic vs. SAP HANA vs. TigerGraph vs. TinkerGraph

System Properties Comparison Faircom DB vs. Heroic vs. SAP HANA vs. TigerGraph vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

www.faircom.com/products/faircom-db

github.com/spotify/heroic

www.sap.com/products/hana.html

www.tigergraph.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

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

spotify.github.io/heroic

help.sap.com/hana

docs.tigergraph.com

Developer

FairCom Corporation

Spotify

SAP

Initial release

1979

2014

2010

2017

2009

Current release

V12, November 2020

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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++

Java

C++

Java

Server operating systems

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

easily portable to other OSs

Appliance or cloud-service

Linux

Data scheme

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

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

via Elasticsearch

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

SQL-like query language (GSQL)

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

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

C++
Java

Groovy
Java

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

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

yes

Role-based access control

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