DBMS > Dgraph vs. Heroic vs. InfluxDB vs. Sadas Engine vs. SAP IQ

System Properties Comparison Dgraph vs. Heroic vs. InfluxDB vs. Sadas Engine vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

DBMS for storing time series, events and metrics

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Columnar RDBMS optimized for Big Data analytics

Primary database model

Graph DBMS

Time Series DBMS

Relational DBMS

column-oriented

Secondary database models

Spatial DBMS

with GEO package

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

dgraph.io

github.com/spotify/heroic

www.influxdata.com/products/influxdb-overview

www.sadasengine.com

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

Technical documentation

dgraph.io/docs

spotify.github.io/heroic

docs.influxdata.com/influxdb

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

help.sap.com/docs/SAP_IQ

Developer

Dgraph Labs, Inc.

Spotify

SADAS s.r.l.

SAP, formerly Sybase

Initial release

2016

2014

2013

2006

1994

Current release

2.7.6, April 2024

8.0

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

free trial version 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

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X

through Homebrew

AIX
Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

SQL-like query language

yes

APIs and other access methods

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

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

HTTP API
JSON over UDP

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

in enterprise version only

horizontal partitioning

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

selectable replication factor

in enterprise version only

none

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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.

yes

Depending on used storage engine

yes

managed by 'Learn by Usage'

User concepts

Access control

Planned for future releases

simple rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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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.

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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