DBMS > Apache Impala vs. Google BigQuery vs. LokiJS vs. MarkLogic vs. TerarkDB

System Properties Comparison Apache Impala vs. Google BigQuery vs. LokiJS vs. MarkLogic vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

Operational and transactional Enterprise NoSQL database

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

Relational DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

impala.apache.org

cloud.google.com/bigquery

github.com/techfort/LokiJS

www.marklogic.com

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

docs.marklogic.com

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Google

MarkLogic Corp.

ByteDance, originally Terark

Initial release

2013

2010

2014

2001

2016

Current release

4.1.0, June 2022

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

commercial

restricted free version is available

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++

JavaScript

C++

Server operating systems

Linux

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL92

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

JavaScript API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

in JavaScript

View functions in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a single collection possible

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

yes, with Range Indexes

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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

Google Cloud Identity & Access Management (IAM)

Role-based access control at the document and subdocument levels

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