DBMS > Apache Impala vs. CockroachDB vs. RavenDB vs. Splunk vs. Transbase

System Properties Comparison Apache Impala vs. CockroachDB vs. RavenDB vs. Splunk vs. Transbase

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.

Open Source Operational and Transactional Enterprise NoSQL Document Database

Analytics Platform for Big Data

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

impala.apache.org

www.cockroachlabs.com

ravendb.net

www.splunk.com

www.transaction.de/en/products/transbase.html

Technical documentation

impala.apache.org/impala-docs.html

www.cockroachlabs.com/docs

ravendb.net/docs

docs.splunk.com/Documentation/Splunk

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cockroach Labs

Hibernating Rhinos

Splunk Inc.

Transaction Software GmbH

Initial release

2013

2015

2010

2003

1987

Current release

4.1.0, June 2022

24.1.0, May 2024

5.4, July 2022

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0, commercial license available

Open Source

AGPL version 3, commercial license available

commercial

Limited free edition and free developer edition available

commercial

free development license

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++

C and C++

Server operating systems

Linux

Linux
macOS
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

dynamic schema

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, wire compatible with PostgreSQL

SQL-like query language (RQL)

Splunk Search Processing Language for search commands

yes

APIs and other access methods

JDBC
ODBC

JDBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP REST

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication using RAFT

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

yes

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Role-based access control

Authorization levels configured per client per database

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

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28 November 2017, Datanami

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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29 January 2024, The Register

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5 December 2023, The New Stack

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6 November 2023, AWS Blog

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14 February 2024, InfoQ.com

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3 October 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

RavenDB Adds Graph Queries
15 May 2019, Datanami

How I Created a RavenDB Python Client
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Oren Eini on RavenDB, Including Consistency Guarantees and C# as the Implementation Language
23 May 2022, InfoQ.com

provided by Google News

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