DBMS > HEAVY.AI vs. Lovefield vs. OpenMLDB vs. Trafodion vs. XTDB

System Properties Comparison HEAVY.AI vs. Lovefield vs. OpenMLDB vs. Trafodion vs. XTDB

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

An open-source machine learning database that provides a feature platform for training and inference

Transactional SQL-on-Hadoop DBMS

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

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

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

google.github.io/lovefield

openmldb.ai

trafodion.apache.org

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

Technical documentation

docs.heavy.ai

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

openmldb.ai/docs/zh/main

trafodion.apache.org/documentation.html

www.xtdb.com/docs

Developer

HEAVY.AI, Inc.

Google

4 Paradigm Inc.

Apache Software Foundation, originally developed by HP

Juxt Ltd.

Initial release

2016

2014

2020

2014

2019

Current release

5.10, January 2022

2.1.12, February 2017

2024-2 February 2024

2.3.0, February 2019

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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

C++, Java, Scala

C++, Java

Clojure

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux

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

Data scheme

yes

Fixed schema

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
SQLAlchemy

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Source-replica replication

yes, via HBase

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

Durability

Support for making data persistent

yes

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

yes

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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