DBMS > Apache Impala vs. atoti vs. Bangdb vs. Lovefield

System Properties Comparison Apache Impala vs. atoti vs. Bangdb vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

Object oriented DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

impala.apache.org

atoti.io

bangdb.com

google.github.io/lovefield

Technical documentation

impala.apache.org/impala-docs.html

docs.atoti.io

docs.bangdb.com

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

ActiveViam

Sachin Sinha, BangDB

Google

Initial release

2013

2012

2014

Current release

4.1.0, June 2022

BangDB 2.0, October 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free versions available

Open Source

BSD 3

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C, C++

JavaScript

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

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

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

Multidimensional Expressions (MDX)

SQL like support with command line tool

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Python

Triggers

yes, Notifications (with Streaming only)

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

using MemoryDB

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 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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
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