DBMS > Apache Spark (SQL) vs. Bangdb vs. GridDB

System Properties Comparison Apache Spark (SQL) vs. Bangdb vs. GridDB

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Editorial information provided by DB-Engines

Name

Description

Apache Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

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	16.73
Rank	#35	Overall
	#20	Relational DBMS

Score	0.06
Rank	#353	Overall
	#48	Document stores
	#36	Graph DBMS
	#35	Time Series DBMS

Score	1.90
Rank	#123	Overall
	#10	Time Series DBMS

Website

spark.apache.org/sql

bangdb.com

griddb.net

Technical documentation

spark.apache.org/docs/latest/sql-programming-guide.html

docs.bangdb.com

docs.griddb.net

Developer

Apache Software Foundation

Sachin Sinha, BangDB

Toshiba Corporation

Initial release

2014

2012

2013

Current release

3.5.0 ( 2.13), September 2023

BangDB 2.0, October 2021

5.1, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD 3

Open Source

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

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C, C++

C++

Server operating systems

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

numerical, string, blob, geometry, boolean, timestamp

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 DML and DDL statements

SQL like support with command line tool

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Supported programming languages

Java
Python
R
Scala

C
C#
C++
Java
Python

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

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Source-replica replication

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

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 can be defined per database

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More resources

Recent citations in the news

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
30 September 2024, Simplilearn

Use Amazon Athena with Spark SQL for your open-source transactional table formats
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Performant IPv4 Range Spark Joins
24 January 2024, Towards Data Science

Amazon EMR 7.1 runtime for Apache Spark and Iceberg can run Spark workloads 2.7 times faster than Apache Spark 3.5.1 and Iceberg 1.5.2
26 August 2024, AWS Blog

provided by Google News

TOSHIBA DIGITAL SOLUTIONS CORPORATION
1 November 2020, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

Amazon Proposes to Develop New Data Center Campus in Virginia
26 August 2022, w.media

IoT: Opt for the Right Open Source Database
11 August 2023, Open Source For You

| TOSHIBA DIGITAL SOLUTIONS CORPORATION
30 October 2020, global.toshiba

provided by Google News

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