DBMS > BigObject vs. Geode vs. GreptimeDB vs. GridGain vs. STSdb

System Properties Comparison BigObject vs. Geode vs. GreptimeDB vs. GridGain vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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

GridGain is an in-memory computing platform, built on Apache Ignite

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Key-value store
Relational DBMS

Key-value store

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

docs.bigobject.io

geode.apache.org/docs

docs.greptime.com

www.gridgain.com/docs/index.html

Developer

BigObject, Inc.

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Greptime Inc.

GridGain Systems, Inc.

STS Soft SC

Initial release

2015

2002

2022

2007

2011

Current release

1.1, February 2017

GridGain 8.5.1

4.0.8, September 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

commercial

Open Source

GPLv2, commercial license 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

Java, C++, .Net

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

the JDK (8 or later) is also required

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements

SQL-like query language (OQL)

yes

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

gRPC
HTTP API
JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

.NET Client API

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

C++
Erlang
Go
Java
JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

C#
Java

Server-side scripts

Stored procedures

Lua

user defined functions

Python

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

Cache Event Listeners

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

Access rights per client and object definable

Simple rights management via user accounts

Security Hooks for custom implementations

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
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Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Typical application scenarios

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