DBMS > ArcadeDB vs. Databend vs. Google BigQuery vs. SAP HANA

System Properties Comparison ArcadeDB vs. Databend vs. Google BigQuery vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Large scale data warehouse service with append-only tables

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Website

arcadedb.com

github.com/datafuselabs/databend
www.databend.com

cloud.google.com/bigquery

www.sap.com/products/hana.html

Technical documentation

docs.arcadedb.com

docs.databend.com

cloud.google.com/bigquery/docs

help.sap.com/hana

Developer

Arcade Data

Databend Labs

Google

SAP

Initial release

2021

2010

Current release

September 2021

1.0.59, April 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Rust

Server operating systems

All OS with a Java VM

hosted
Linux
macOS

hosted

Appliance or cloud-service

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

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
Python
Rust

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

yes

Since BigQuery is designed for querying 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

User concepts

Access control

Users with fine-grained authorization concept, user roles

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

Google Cloud Identity & Access Management (IAM)

yes

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