DBMS > GreptimeDB vs. Heroic vs. Infobright vs. searchxml vs. TinkerGraph

System Properties Comparison GreptimeDB vs. Heroic vs. Infobright vs. searchxml vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

DBMS for structured and unstructured content wrapped with an application server

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Time Series DBMS

Relational DBMS

Native XML DBMS
Search engine

Graph DBMS

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

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Website

greptime.com

github.com/spotify/heroic

ignitetech.com/softwarelibrary/infobrightdb

www.searchxml.net/category/products

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.greptime.com

spotify.github.io/heroic

www.searchxml.net/support/handouts

Developer

Greptime Inc.

Spotify

Ignite Technologies Inc.; formerly InfoBright Inc.

informationpartners gmbh

Initial release

2022

2014

2005

2015

2009

Current release

1.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

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

Rust

Java

C++

Java

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
Windows

Windows

Data scheme

schema-free, schema definition possible

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

via Elasticsearch

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
HTTP API
JDBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API
WebDAV
XQuery
XSLT

TinkerPop 3

Supported programming languages

C++
Erlang
Go
Java
JavaScript

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

most other programming languages supported via APIs

Groovy
Java

Server-side scripts

Stored procedures

Python

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional

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

exploiting MySQL or PostgreSQL frontend capabilities

Domain, group and role-based access control at the document level and for application services

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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More resources

Recent citations in the news

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune
3 June 2024, AWS Blog

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

provided by Google News

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