DBMS > Apache Impala vs. Fauna vs. GeoSpock vs. Lovefield vs. TerarkDB

System Properties Comparison Apache Impala vs. Fauna vs. GeoSpock vs. Lovefield vs. TerarkDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Spatial and temporal data processing engine for extreme data scale

Embeddable relational database for web apps written in pure JavaScript

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store

Time Series DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

impala.apache.org

fauna.com

geospock.com

google.github.io/lovefield

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

docs.fauna.com

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Fauna, Inc.

GeoSpock

Google

ByteDance, originally Terark

Initial release

2013

2014

2016

Current release

4.1.0, June 2022

2.0, September 2019

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Scala

Java, Javascript

JavaScript

C++

Server operating systems

Linux

hosted

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

temporal, categorical

yes

SQL

Support of SQL

SQL-like DML and DDL statements

ANSI SQL for query only (using Presto)

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

JavaScript

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

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

Immediate Consistency

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

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Identity management, authentication, and access control

Access rights for users can be defined per table

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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
12 March 2017, Uber

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3 February 2024, SiliconANGLE News

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21 March 2024, GlobeNewswire

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22 August 2023, Business Wire

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17 October 2023, Utah Division of Wildlife Resources

CITES Trade Database surpasses 25 million trade transaction records
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How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

Cambridge-based data analytics startup GeoSpock lands €4.6 million
2 October 2020, EU-Startups

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

provided by Google News

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