DBMS > EventStoreDB vs. GreptimeDB vs. Microsoft Azure Cosmos DB vs. Sqrrl vs. TinkerGraph

System Properties Comparison EventStoreDB vs. GreptimeDB vs. Microsoft Azure Cosmos DB vs. Sqrrl vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Globally distributed, horizontally scalable, multi-model database service

Adaptable, secure NoSQL built on Apache Accumulo

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

Primary database model

Event Store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

www.eventstore.com

greptime.com

azure.microsoft.com/services/cosmos-db

sqrrl.com

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

Technical documentation

developers.eventstore.com

docs.greptime.com

learn.microsoft.com/azure/cosmos-db

Developer

Event Store Limited

Greptime Inc.

Microsoft

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2022

2014

2012

2009

Current release

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

Java

Server operating systems

Linux
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

hosted

Linux

Data scheme

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

gRPC
HTTP API
JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

TinkerPop 3

Supported programming languages

C++
Erlang
Go
Java
JavaScript

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Groovy
Java

Server-side scripts

Stored procedures

Python

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

making use of Hadoop

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

making use of Hadoop

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

Atomic updates per row, document, or graph entity

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

Access rights can be defined down to the item level

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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...
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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...
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