DBMS > Bangdb vs. Blazegraph vs. Databend vs. Drizzle vs. Hyprcubd

System Properties Comparison Bangdb vs. Blazegraph vs. Databend vs. Drizzle vs. Hyprcubd

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Serverless Time Series DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Graph DBMS
RDF store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Website

bangdb.com

blazegraph.com

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

hyprcubd.com (offline)

Technical documentation

docs.bangdb.com

wiki.blazegraph.com

docs.databend.com

Developer

Sachin Sinha, BangDB

Blazegraph

Databend Labs

Drizzle project, originally started by Brian Aker

Hyprcubd, Inc.

Initial release

2012

2006

2021

2008

Current release

BangDB 2.0, October 2021

2.1.5, March 2019

1.0.59, April 2023

7.2.4, September 2012

License

Commercial or Open Source

Open Source

BSD 3

Open Source

extended commercial license available

Open Source

Apache Version 2.0

Open Source

GNU GPL

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.

Implementation language

C, C++

Java

Rust

C++

Server operating systems

Linux

Linux
OS X
Windows

hosted
Linux
macOS

FreeBSD
Linux
OS X

hosted

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

RDF literal types

yes

time, int, uint, float, string

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SPARQL is used as query language

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

CLI Client
JDBC
RESTful HTTP API

JDBC

gRPC (https)

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Security and Authentication via Web Application Container (Tomcat, Jetty)

Users with fine-grained authorization concept, user roles

Pluggable authentication mechanisms

e.g. LDAP, HTTP

token access

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