DBMS > Apache Impala vs. Bangdb vs. EJDB vs. Newts

System Properties Comparison Apache Impala vs. Bangdb vs. EJDB vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Time Series DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

impala.apache.org

bangdb.com

github.com/Softmotions/ejdb

opennms.github.io/newts

Technical documentation

impala.apache.org/impala-docs.html

docs.bangdb.com

github.com/Softmotions/ejdb/blob/master/README.md

github.com/OpenNMS/newts/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Sachin Sinha, BangDB

Softmotions

OpenNMS Group

Initial release

2013

2012

2014

Current release

4.1.0, June 2022

BangDB 2.0, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSD 3

Open Source

GPLv2

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

C, C++

Java

Server operating systems

Linux

server-less

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes

string, integer, double, bool, date, object_id

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

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

SQL like support with command line tool

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

in-process shared library

HTTP REST
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Read/Write Locking

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes (enterprise version only)

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More resources

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Farewell, Froggy: The Age of Ribbit Is Nearing an End
25 May 2013, Mother Jones

provided by Google News

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