DBMS > Datomic vs. Google BigQuery vs. LevelDB vs. OpenTSDB

System Properties Comparison Datomic vs. Google BigQuery vs. LevelDB vs. OpenTSDB

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Large scale data warehouse service with append-only tables

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Scalable Time Series DBMS based on HBase

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Website

www.datomic.com

cloud.google.com/bigquery

github.com/google/leveldb

opentsdb.net

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

Cognitect

Google

currently maintained by Yahoo and other contributors

Initial release

2012

2010

2011

Current release

1.0.6735, June 2023

1.23, February 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD

Open Source

LGPL

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Java

Server operating systems

All OS with a Java VM

hosted

Illumos
Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

HTTP API
Telnet API

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Erlang
Go
Java
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

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