DBMS > Apache Impala vs. CockroachDB vs. H2GIS vs. Oracle Berkeley DB vs. Realm

System Properties Comparison Apache Impala vs. CockroachDB vs. H2GIS vs. Oracle Berkeley DB vs. Realm

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Spatial extension of H2

Widely used in-process key-value store

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Spatial DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Secondary database models

Document store

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

impala.apache.org

www.cockroachlabs.com

www.h2gis.org

www.oracle.com/database/technologies/related/berkeleydb.html

realm.io

Technical documentation

impala.apache.org/impala-docs.html

www.cockroachlabs.com/docs

www.h2gis.org/docs/home

docs.oracle.com/cd/E17076_05/html/index.html

realm.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cockroach Labs

CNRS

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Realm, acquired by MongoDB in May 2019

Initial release

2013

2015

2013

1994

2014

Current release

4.1.0, June 2022

24.1.0, May 2024

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0, commercial license available

Open Source

LGPL 3.0

Open Source

commercial license available

Open Source

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, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

Linux
macOS
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

dynamic schema

yes

schema-free

yes

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, wire compatible with PostgreSQL

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
ODBC

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

Java

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

based on H2

runs within the applications so server-side scripts are unnecessary

Triggers

yes

only for the SQL API

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using RAFT

yes

based on H2

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

In-Memory realm

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role-based access control

yes

based on H2

yes

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