DBMS > Apache Impala vs. Axibase vs. BigObject vs. EventStoreDB vs. MarkLogic

System Properties Comparison Apache Impala vs. Axibase vs. BigObject vs. EventStoreDB vs. MarkLogic

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Analytic DBMS for real-time computations and queries

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

Operational and transactional Enterprise NoSQL database

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Event Store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	0.32
Rank	#288	Overall
	#25	Time Series DBMS

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	6.50
Rank	#56	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#5	Search engines

Website

impala.apache.org

axibase.com/docs/atsd/finance

bigobject.io

www.eventstore.com

www.marklogic.com

Technical documentation

impala.apache.org/impala-docs.html

docs.bigobject.io

developers.eventstore.com

docs.marklogic.com

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Axibase Corporation

BigObject, Inc.

Event Store Limited

MarkLogic Corp.

Initial release

2013

2015

2012

2001

Current release

4.1.0, June 2022

15585

21.2, February 2021

11.0, December 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free community edition available

Open Source

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

SQL-like DML and DDL statements

yes

SQL92

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

fluentd
ODBC
RESTful HTTP 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

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Lua

yes

via XQuery or JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

none

yes

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role-based access control at the document and subdocument levels

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More resources

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