DBMS > BigchainDB vs. Google Cloud Datastore vs. JanusGraph vs. SAP HANA vs. YDB

System Properties Comparison BigchainDB vs. Google Cloud Datastore vs. JanusGraph vs. SAP HANA vs. YDB

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store

Graph DBMS

Relational DBMS

Document store
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	0.85
Rank	#208	Overall
	#35	Document stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

www.bigchaindb.com

cloud.google.com/datastore

janusgraph.org

www.sap.com/products/hana.html

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/datastore/docs

docs.janusgraph.org

help.sap.com/hana

ydb.tech/en/docs

Developer

Google

Linux Foundation; originally developed as Titan by Aurelius

SAP

Yandex

Initial release

2016

2008

2017

2010

2019

Current release

0.6.3, February 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0; commercial license available

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

Python

Java

Server operating systems

Linux

hosted

Linux
OS X
Unix
Windows

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes, details here

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 (GQL)

yes

SQL-like query language (YQL)

APIs and other access methods

CLI Client
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Clojure
Java
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

using Google App Engine

yes

SQLScript, R

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using Paxos

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

User authentification and security via Rexster Graph Server

yes

Access rights defined for Yandex Cloud users

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