DBMS > Apache Drill vs. EJDB vs. Google BigQuery vs. OpenTSDB vs. Prometheus

System Properties Comparison Apache Drill vs. EJDB vs. Google BigQuery vs. OpenTSDB vs. Prometheus

Editorial information provided by DB-Engines

Name

Description

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

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

Large scale data warehouse service with append-only tables

Scalable Time Series DBMS based on HBase

Open-source Time Series DBMS and monitoring system

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

Time Series DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

drill.apache.org

github.com/Softmotions/ejdb

cloud.google.com/bigquery

opentsdb.net

prometheus.io

Technical documentation

drill.apache.org/docs

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

cloud.google.com/bigquery/docs

opentsdb.net/docs/build/html/index.html

prometheus.io/docs

Developer

Apache Software Foundation

Softmotions

Google

currently maintained by Yahoo and other contributors

Initial release

2012

2010

2011

2015

Current release

1.20.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2

commercial

Open Source

LGPL

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

Java

Server operating systems

Linux
OS X
Windows

server-less

hosted

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

numeric data for metrics, strings for tags

Numeric data only

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.

Import of XML data possible

Secondary indexes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

in-process shared library

RESTful HTTP/JSON API

HTTP API
Telnet API

RESTful HTTP/JSON API

Supported programming languages

C++

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

none

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

User concepts

Access control

Depending on the underlying data source

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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