DBMS > Badger vs. Google BigQuery vs. SAP HANA vs. TinkerGraph

System Properties Comparison Badger vs. Google BigQuery vs. SAP HANA vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Large scale data warehouse service with append-only tables

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

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Key-value store

Relational DBMS

Graph 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	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

github.com/dgraph-io/badger

cloud.google.com/bigquery

www.sap.com/products/hana.html

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

godoc.org/github.com/dgraph-io/badger

cloud.google.com/bigquery/docs

help.sap.com/hana

Developer

DGraph Labs

Google

SAP

Initial release

2017

2010

2009

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Appliance or cloud-service

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Groovy
Java

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

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