DBMS > BigObject vs. EJDB vs. GreptimeDB vs. Ignite vs. TimescaleDB

System Properties Comparison BigObject vs. EJDB vs. GreptimeDB vs. Ignite vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Time Series DBMS

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

bigobject.io

github.com/Softmotions/ejdb

greptime.com

ignite.apache.org

www.timescale.com

Technical documentation

docs.bigobject.io

github.com/Softmotions/ejdb/blob/master/README.md

docs.greptime.com

apacheignite.readme.io/docs

docs.timescale.com

Developer

BigObject, Inc.

Softmotions

Greptime Inc.

Apache Software Foundation

Timescale

Initial release

2015

2012

2022

2015

2017

Current release

Apache Ignite 2.6

2.15.0, May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

C++, Java, .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)

server-less

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

in-process shared library

gRPC
HTTP API
JDBC

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Erlang
Go
Java
JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

Python

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

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

Source-replica replication with hot standby and reads on replicas

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

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Read/Write Locking

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

Simple rights management via user accounts

Security Hooks for custom implementations

fine grained access rights 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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