DBMS > Graph Engine vs. Spark SQL vs. SQLite vs. STSdb vs. TigerGraph

System Properties Comparison Graph Engine vs. Spark SQL vs. SQLite vs. STSdb vs. TigerGraph

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Widely used embeddable, in-process RDBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Graph 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	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.graphengine.io

spark.apache.org/sql

www.sqlite.org

github.com/STSSoft/STSdb4

www.tigergraph.com

Technical documentation

www.graphengine.io/docs/manual

spark.apache.org/docs/latest/sql-programming-guide.html

www.sqlite.org/docs.html

docs.tigergraph.com

Developer

Microsoft

Apache Software Foundation

Dwayne Richard Hipp

STS Soft SC

Initial release

2010

2014

2000

2011

2017

Current release

3.5.0 ( 2.13), September 2023

3.45.3 (15 April 2024), April 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

Scala

C++

Server operating systems

.NET

Linux
OS X
Windows

server-less

Windows

Linux

Data scheme

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.NET Client API

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

Supported programming languages

C#
C++
F#
Visual Basic

Java
Python
R
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C#
Java

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

via file-system locks

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

User concepts

Access control

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.