DBMS > Bangdb vs. GridDB vs. HarperDB vs. SiriDB

System Properties Comparison Bangdb vs. GridDB vs. HarperDB vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

Open Source Time Series DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

Key-value store
Relational DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

Technical documentation

docs.bangdb.com

docs.griddb.net

docs.harperdb.io/docs

docs.siridb.com

Developer

Sachin Sinha, BangDB

Toshiba Corporation

HarperDB

Cesbit

Initial release

2012

2013

2017

Current release

BangDB 2.0, October 2021

5.1, August 2022

3.1, August 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

free community edition available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Node.js

Server operating systems

Linux

Linux
OS X

Linux

Data scheme

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

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

yes

numerical, string, blob, geometry, boolean, timestamp

yes

JSON data types

yes

Numeric data

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

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like data manipulation statements

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

HTTP API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Triggers

yes, Notifications (with Streaming only)

yes

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

A table resides as a whole on one (or more) nodes in a cluster

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

yes

the nodes on which a table resides can be defined

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID at container level

Atomic execution of specific operations

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

yes, using LMDB

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

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users can be defined per database

Access rights for users and roles

simple rights management via user accounts

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