DBMS > Databricks vs. GreptimeDB vs. HEAVY.AI vs. SQLite

System Properties Comparison Databricks vs. GreptimeDB vs. HEAVY.AI vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

www.databricks.com

greptime.com

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

www.sqlite.org

Technical documentation

docs.databricks.com

docs.greptime.com

docs.heavy.ai

www.sqlite.org/docs.html

Developer

Databricks

Greptime Inc.

HEAVY.AI, Inc.

Dwayne Richard Hipp

Initial release

2013

2022

2016

2000

Current release

5.10, January 2022

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

C++ and CUDA

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

server-less

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free, schema definition possible

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP API
JDBC

JDBC
ODBC
Thrift
Vega

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Python
R
Scala

C++
Erlang
Go
Java
JavaScript

All languages supporting JDBC/ODBC/Thrift
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

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

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
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Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
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