DBMS > EDB Postgres vs. HEAVY.AI vs. Lovefield vs. XTDB

System Properties Comparison EDB Postgres vs. HEAVY.AI vs. Lovefield vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.enterprisedb.com

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.enterprisedb.com/docs

docs.heavy.ai

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

www.xtdb.com/docs

Developer

EnterpriseDB

HEAVY.AI, Inc.

Google

Juxt Ltd.

Initial release

2005

2016

2014

2019

Current release

14, December 2021

5.10, January 2022

2.1.12, February 2017

1.19, September 2021

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

MIT License

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++ and CUDA

JavaScript

Clojure

Server operating systems

Linux
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-like query language

via JavaScript builder pattern

limited SQL, making use of Apache Calcite

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift
Vega

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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

EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack
22 April 2024, Datanami

EDB Is Developing Its Flagship Database Into A Comprehensive Platform For Analytics, AI
27 February 2024, CRN

Key new features and innovations in EDB Postgres 16
1 December 2023, InfoWorld

EDB Closes the High Availability Gap for Postgres in the Cloud with EDB Postgres Distributed on BigAnimal
29 August 2023, GlobeNewswire

EDB Introduces Two New Ways to Get Postgres in AWS Marketplace
28 November 2023, Yahoo Finance

provided by Google News

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Making the most of geospatial intelligence
14 April 2023, InfoWorld

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

Share this page