DBMS > AnzoGraph DB vs. Heroic vs. ObjectBox vs. Sadas Engine vs. SQream DB

System Properties Comparison AnzoGraph DB vs. Heroic vs. ObjectBox vs. Sadas Engine vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

Extremely fast embedded database for small devices, IoT and Mobile

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

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

cambridgesemantics.com/anzograph

github.com/spotify/heroic

objectbox.io

www.sadasengine.com

sqream.com

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

spotify.github.io/heroic

docs.objectbox.io

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

docs.sqream.com

Developer

Cambridge Semantics

Spotify

ObjectBox Limited

SADAS s.r.l.

SQream Technologies

Initial release

2018

2014

2017

2006

2017

Current release

2.3, January 2021

8.0

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache License 2.0

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 and C++

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

Android
iOS
Linux
macOS
Windows

AIX
Linux
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

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

Proprietary native API

JDBC
ODBC
Proprietary protocol

.Net
JDBC
ODBC

Supported programming languages

C++
Java
Python

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions in Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

none

horizontal partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users and roles

yes

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

More information provided by the system vendor

News

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable?
19 September 2018, Forbes

provided by Google News

SQream Announces Strategic Integration for Powerful Big Data Analytics with Dataiku
9 February 2024, insideBIGDATA

I SQream, you SQream, we all SQream for … data analytics?
5 October 2023, Fierce Network

SQream Technologies raises $39.4 million for GPU-accelerated databases
24 June 2020, VentureBeat

SQream Announces Free Licenses to Organizations Using Data Analytics to Fight the Coronavirus
9 April 2020, Embedded Computing Design

Chinese giant Alibaba leads investment round in Israel big-data startup
30 May 2018, The Times of Israel

provided by Google News

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