DBMS > GreptimeDB vs. Hazelcast vs. Heroic vs. Ingres vs. Percona Server for MongoDB

System Properties Comparison GreptimeDB vs. Hazelcast vs. Heroic vs. Ingres vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted in-memory data grid

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

Well established RDBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

greptime.com

hazelcast.com

github.com/spotify/heroic

www.actian.com/databases/ingres

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

docs.greptime.com

hazelcast.org/imdg/docs

spotify.github.io/heroic

docs.actian.com/ingres

docs.percona.com/percona-distribution-for-mongodb

Developer

Greptime Inc.

Hazelcast

Spotify

Actian Corporation

Percona

Initial release

2022

2008

2014

1974

originally developed at University Berkely in early 1970s

2015

Current release

5.3.6, November 2023

11.2, May 2022

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

commercial

Open Source

GPL Version 2

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++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

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

the object must implement a serialization strategy

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP API
JDBC

JCache
JPA
Memcached protocol
RESTful HTTP API

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

proprietary protocol using JSON

Supported programming languages

C++
Erlang
Go
Java
JavaScript

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

Python

yes

Event Listeners, Executor Services

yes

JavaScript

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

Ingres Replicator

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

via In-Memory Engine

User concepts

Access control

Simple rights management via user accounts

Role-based access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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