DBMS > HEAVY.AI vs. Lovefield vs. Memcached vs. XTDB

System Properties Comparison HEAVY.AI vs. Lovefield vs. Memcached vs. XTDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

In-memory key-value store, originally intended for caching

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

Primary database model

Relational DBMS

Key-value store

Document store

Secondary database models

Spatial DBMS

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

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	20.74
Rank	#32	Overall
	#4	Key-value stores

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

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

google.github.io/lovefield

www.memcached.org

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

Technical documentation

docs.heavy.ai

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

github.com/memcached/memcached/wiki

www.xtdb.com/docs

Developer

HEAVY.AI, Inc.

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Juxt Ltd.

Initial release

2016

2014

2003

2019

Current release

5.10, January 2022

2.1.12, February 2017

1.6.25, March 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

BSD license

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

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Unix
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC
Thrift
Vega

Proprietary protocol

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Repcached, a Memcached patch, provides this functionallity

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

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

yes

using SASL (Simple Authentication and Security Layer) protocol

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

DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the 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 Launches Industry's First Digital Twin for Telco Network Planning, Building and Operations
20 September 2022, Datanami

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

provided by Google News

Why DDoS Threat Actors Are Shifting Their Tactics
15 March 2024, Infosecurity Magazine

The Performance Impact Of Intel's Register File Data Sampling
15 March 2024, Phoronix

What are memcached servers, and why are they being used to launch record-setting DDoS attacks?
6 March 2018, GeekWire

Memcached DDoS: The biggest, baddest denial of service attacker yet
1 March 2018, ZDNet

Why Redis beats Memcached for caching
14 September 2017, InfoWorld

provided by Google News

Share this page