DBMS > Bangdb vs. Google Cloud Spanner vs. IRONdb vs. jBASE

System Properties Comparison Bangdb vs. Google Cloud Spanner vs. IRONdb vs. jBASE

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Editorial information provided by DB-Engines

Name

IRONdb 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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

bangdb.com

cloud.google.com/spanner

www.circonus.com/solutions/time-series-database/

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

docs.bangdb.com

cloud.google.com/spanner/docs

docs.circonus.com/irondb/category/getting-started

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Sachin Sinha, BangDB

Google

Circonus LLC.

Rocket Software (formerly Zumasys)

Initial release

2012

2017

1991

Current release

BangDB 2.0, October 2021

V0.10.20, January 2018

5.7

License

Commercial or Open Source

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C and C++

Server operating systems

Linux

hosted

Linux

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

text, numeric, histograms

optional

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.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

Query statements complying to ANSI 2011

SQL-like query language (Circonus Analytics Query Language: CAQL)

Embedded SQL for jBASE in BASIC

APIs and other access methods

Proprietary protocol
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
C#
C++
Java
Python

Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

yes, in Lua

yes

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

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication with 3 replicas for regional instances.

configurable replication factor, datacenter aware

yes

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

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

yes

User concepts

Access control

yes (enterprise version only)

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

Access rights can be defined down to the item level

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