DBMS > Dragonfly vs. Google BigQuery vs. HBase vs. SAP HANA

System Properties Comparison Dragonfly vs. Google BigQuery vs. HBase vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Large scale data warehouse service with append-only tables

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

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	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

cloud.google.com/bigquery

hbase.apache.org

www.sap.com/products/hana.html

Technical documentation

www.dragonflydb.io/docs

cloud.google.com/bigquery/docs

hbase.apache.org/book.html

help.sap.com/hana

Developer

DragonflyDB team and community contributors

Google

Apache Software Foundation

Apache top-level project, originally developed by Powerset

SAP

Initial release

2023

2010

2008

2010

Current release

1.0, March 2023

2.3.4, January 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Open Source

Apache version 2

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

C++

Java

Server operating systems

Linux

hosted

Linux
Unix
Windows

using Cygwin

Appliance or cloud-service

Data scheme

scheme-free

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes

options to bring your own types, AVRO

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

Proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP/JSON API

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Groovy
Java
PHP
Python
Scala

Server-side scripts

Stored procedures

Lua

user defined functions

in JavaScript

yes

Coprocessors in Java

SQLScript, R

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

Since BigQuery is designed for querying data

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

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

Password-based authentication

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

Google Cloud Identity & Access Management (IAM)

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

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