DBMS > Axibase vs. Badger vs. GreptimeDB vs. HEAVY.AI vs. Sadas Engine

System Properties Comparison Axibase vs. Badger vs. GreptimeDB vs. HEAVY.AI vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

axibase.com/docs/atsd/finance

github.com/dgraph-io/badger

greptime.com

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

www.sadasengine.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.greptime.com

docs.heavy.ai

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Axibase Corporation

DGraph Labs

Greptime Inc.

HEAVY.AI, Inc.

SADAS s.r.l.

Initial release

2013

2017

2022

2016

2006

Current release

15585

5.10, January 2022

8.0

License

Commercial or Open Source

commercial

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

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

free trial version available

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

Rust

C++ and CUDA

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

AIX
Linux
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

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

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC
HTTP API
JDBC

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
Proprietary protocol

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C++
Erlang
Go
Java
JavaScript

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Concurrency

Support for concurrent manipulation of data

yes

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

managed by 'Learn by Usage'

User concepts

Access control

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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