DBMS > BigchainDB vs. ClickHouse vs. Google Cloud Datastore vs. Heroic vs. SAP Advantage Database Server

System Properties Comparison BigchainDB vs. ClickHouse vs. Google Cloud Datastore vs. Heroic vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

www.bigchaindb.com

clickhouse.com

cloud.google.com/datastore

github.com/spotify/heroic

www.sap.com/products/advantage-database-server.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

clickhouse.com/docs

cloud.google.com/datastore/docs

spotify.github.io/heroic

Developer

Clickhouse Inc.

Google

Spotify

Sybase, SAP

Initial release

2016

2008

2014

1993

Current release

v24.4.1.2088-stable, May 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

Python

C++

Java

Server operating systems

Linux

FreeBSD
Linux
macOS

hosted

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

via Elasticsearch

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language (GQL)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

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

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

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

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

using Google App Engine

yes

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication using Paxos

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

In-memory capabilities

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

yes

caching of (temporary) tables can be configured

User concepts

Access control

yes

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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

fine grained access rights according to SQL-standard

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