DBMS > Dgraph vs. EsgynDB vs. GeoMesa vs. SAP IQ vs. Spark SQL

System Properties Comparison Dgraph vs. EsgynDB vs. GeoMesa vs. SAP IQ vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

column-oriented

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

dgraph.io

www.esgyn.cn

www.geomesa.org

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

spark.apache.org/sql

Technical documentation

dgraph.io/docs

www.geomesa.org/documentation/stable/user/index.html

help.sap.com/docs/SAP_IQ

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

Developer

Dgraph Labs, Inc.

Esgyn

CCRi and others

SAP, formerly Sybase

Apache Software Foundation

Initial release

2016

2015

2014

1994

2014

Current release

5.0.0, May 2024

16.1 SPS04, April 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache License 2.0

commercial

Open Source

Apache 2.0

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

C++, Java

Scala

Server operating systems

Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Java
Perl
PHP
Python
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

depending on storage layer

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

depending on storage layer

SAP/Sybase Replication Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

depending on storage layer

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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