DBMS > Citus vs. HEAVY.AI vs. JSqlDb vs. Lovefield vs. XTDB

System Properties Comparison Citus vs. HEAVY.AI vs. JSqlDb vs. Lovefield vs. XTDB

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

JavaScript Query Language Database, stores JavaScript objects and primitives

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
Object oriented DBMS

Relational DBMS

Document store

Secondary database models

Document store

Spatial DBMS

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

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.citusdata.com

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

jsqldb.org (offline)

google.github.io/lovefield

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

Technical documentation

docs.citusdata.com

docs.heavy.ai

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

www.xtdb.com/docs

Developer

HEAVY.AI, Inc.

Konrad von Backstrom

Google

Juxt Ltd.

Initial release

2010

2016

2018

2014

2019

Current release

8.1, December 2018

5.10, January 2022

0.8, December 2018

2.1.12, February 2017

1.19, September 2021

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

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

Linux
macOS
Windows

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

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
JavaScript (Node.js)
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.

functions in JavaScript

Triggers

yes

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

Source-replica replication

other methods possible by using 3rd party extensions

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

Durability

Support for making data persistent

yes

using RocksDB

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

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