DBMS > Axibase vs. Google Cloud Bigtable vs. PlanetScale vs. RocksDB vs. Splunk

System Properties Comparison Axibase vs. Google Cloud Bigtable vs. PlanetScale vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Scalable, distributed, serverless MySQL database platform built on top of Vitess

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

Analytics Platform for Big Data

Primary database model

Time Series DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

axibase.com/docs/atsd/finance

cloud.google.com/bigtable

planetscale.com

rocksdb.org

www.splunk.com

Technical documentation

cloud.google.com/bigtable/docs

planetscale.com/docs

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Axibase Corporation

Google

PlanetScale

Facebook, Inc.

Splunk Inc.

Initial release

2013

2015

2020

2013

2003

Current release

15585

9.2.1, May 2024

License

Commercial or Open Source

commercial

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

commercial

Open Source

BSD

commercial

Limited free edition and free developer edition 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

Java

C++

Server operating systems

Linux

hosted

Docker
Linux
macOS

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

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 query language

yes

with proprietary extensions

Splunk Search Processing Language for search commands

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
MySQL protocol
ODBC

C++ API
Java API

HTTP REST

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication
Source-replica replication

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency across shards
Immediate Consistency within a shard

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-row operations

ACID at shard level

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

table locks or row locks depending on storage engine

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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