DBMS > Dgraph vs. Google BigQuery vs. InterSystems IRIS vs. Postgres-XL vs. Warp 10

System Properties Comparison Dgraph vs. Google BigQuery vs. InterSystems IRIS vs. Postgres-XL vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Graph DBMS

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

dgraph.io

cloud.google.com/bigquery

www.intersystems.com/products/intersystems-iris

www.postgres-xl.org

www.warp10.io

Technical documentation

dgraph.io/docs

cloud.google.com/bigquery/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

www.postgres-xl.org/documentation

www.warp10.io/content/02_Getting_started

Developer

Dgraph Labs, Inc.

Google

InterSystems

SenX

Initial release

2016

2010

2018

2014

since 2012, originally named StormDB

2015

Current release

2023.3, June 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla public license

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux
OS X
Windows

hosted

AIX
Linux
macOS
Ubuntu
Windows

Linux
macOS

Linux
OS X
Windows

Data scheme

schema-free

yes

depending on used data model

yes

schema-free

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

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

HTTP API
Jupyter
WebSocket

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

MVCC

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.

yes

User concepts

Access control

Planned for future releases

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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