DBMS > CrateDB vs. Microsoft Azure Table Storage vs. RocksDB vs. Splunk vs. TerarkDB

System Properties Comparison CrateDB vs. Microsoft Azure Table Storage vs. RocksDB vs. Splunk vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

A Wide Column Store for rapid development using massive semi-structured datasets

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Analytics Platform for Big Data

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

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

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

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

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

Website

cratedb.com

azure.microsoft.com/en-us/services/storage/tables

rocksdb.org

www.splunk.com

github.com/bytedance/terarkdb

Technical documentation

cratedb.com/docs

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Crate

Microsoft

Facebook, Inc.

Splunk Inc.

ByteDance, originally Terark

Initial release

2013

2012

2013

2003

2016

Current release

8.11.4, April 2024

License

Commercial or Open Source

Open Source

commercial

Open Source

BSD

commercial

Limited free edition and free developer edition 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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux

Linux
OS X
Solaris
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

RESTful HTTP API

C++ API
Java API

HTTP REST

C++ API
Java API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

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

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

optimistic locking

yes

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

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.

yes

User concepts

Access control

rights management via user accounts

Access rights based on private key authentication or shared access signatures

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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Licensing and pricing models

See CrateDB pricing >
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