DBMS > Axibase vs. Drizzle vs. HEAVY.AI vs. Lovefield

System Properties Comparison Axibase vs. Drizzle vs. HEAVY.AI vs. Lovefield

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

axibase.com/docs/atsd/finance

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

google.github.io/lovefield

Technical documentation

docs.heavy.ai

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

Developer

Axibase Corporation

Drizzle project, originally started by Brian Aker

HEAVY.AI, Inc.

Google

Initial release

2013

2008

2016

2014

Current release

15585

7.2.4, September 2012

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

GNU GPL

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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

Java

C++

C++ and CUDA

JavaScript

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

JDBC
ODBC
Thrift
Vega

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C++
Java
PHP

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

hooks for callbacks inside the server can be used.

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

Multi-source replication
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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More resources

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