DBMS > Apache Drill vs. EventStoreDB vs. Google Cloud Datastore vs. TerarkDB

System Properties Comparison Apache Drill vs. EventStoreDB vs. Google Cloud Datastore vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Relational DBMS

Event Store

Document store

Key-value store

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

drill.apache.org

www.eventstore.com

cloud.google.com/datastore

github.com/bytedance/terarkdb

Technical documentation

drill.apache.org/docs

developers.eventstore.com

cloud.google.com/datastore/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Event Store Limited

Google

ByteDance, originally Terark

Initial release

2012

2008

2016

Current release

1.20.3, January 2023

21.2, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

commercial

restricted open source version available

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

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

hosted

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language (GQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

C++ API
Java API

Supported programming languages

C++

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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