DBMS > Apache Impala vs. FoundationDB vs. ObjectBox

System Properties Comparison Apache Impala vs. FoundationDB vs. ObjectBox

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Analytic DBMS for Hadoop

Ordered key-value store. Core features are complimented by layers.

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Object oriented DBMS
Vector DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	12.57
Rank	#40	Overall
	#24	Relational DBMS

Score	1.02
Rank	#185	Overall
	#31	Document stores
	#27	Key-value stores
	#86	Relational DBMS

Score	1.12
Rank	#173	Overall
	#5	Object oriented DBMS
	#8	Vector DBMS

Website

impala.apache.org

github.com/apple/foundationdb

github.com/objectbox
objectbox.io

Technical documentation

impala.apache.org/impala-docs.html

apple.github.io/foundationdb

docs.objectbox.io

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

FoundationDB

ObjectBox Limited

Initial release

2013

2017

Current release

4.1.0, June 2022

6.2.28, November 2020

4.0 (May 2024)

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Bindings are released under Apache 2.0

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C and C++

Server operating systems

Linux

Linux
OS X
Windows

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Data scheme

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support typing

yes, plus "flex" map-like types

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

SQL

Support of SQL

SQL-like DML and DDL statements

supported in specific SQL layer only

APIs and other access methods

JDBC
ODBC

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

in SQL-layer only

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Data sync between devices allowing occasional connected databases to work completely offline

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

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

More information provided by the system vendor

News

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

How different SQL-on-Hadoop engines satisfy BI workloads
24 February 2016, CIO

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

FoundationDB team’s new venture, Antithesis, raises $47M to enhance software testing
13 February 2024, SiliconANGLE News

Antithesis raises $47M to launch an automated testing platform for software
13 February 2024, TechCrunch

FoundationDB, a very interesting NoSQL database owned by Apple, is now an open-source project
19 April 2018, GeekWire

Deno adds scaleable messaging with new Queues feature, sparks debate about proprietary services
28 September 2023, DevClass

IBM Cloudant pulls plan to fund new foundational layer for CouchDB
15 March 2022, The Register

provided by Google News

Industrial IoT (IIoT) edge solution for railway operators – a Kapsch ObjectBox Case Study
21 June 2019, 1E9

provided by Google News

Share this page