DBMS > BoltDB vs. Hazelcast vs. RocksDB vs. SingleStore vs. Splunk

System Properties Comparison BoltDB vs. Hazelcast vs. RocksDB vs. SingleStore vs. Splunk

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

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

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Analytics Platform for Big Data

Primary database model

Key-value store

Relational DBMS

Search engine

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

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

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

github.com/boltdb/bolt

Technical documentation

hazelcast.org/imdg/docs

github.com/facebook/rocksdb/wiki

docs.singlestore.com

docs.splunk.com/Documentation/Splunk

Developer

Hazelcast

Facebook, Inc.

SingleStore Inc.

Splunk Inc.

Initial release

2013

2008

2013

2003

Current release

5.3.6, November 2023

8.11.4, April 2024

8.5, January 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

commercial

free developer edition available

commercial

Limited free edition and free developer edition 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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

Java

C++

C++, Go

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

64 bit version required

Linux
OS X
Solaris
Windows

Data scheme

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

but no triggers and foreign keys

Splunk Search Processing Language for search commands

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

C++ API
Java API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

HTTP REST

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

Bash
C
C#
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

hash partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Replicated Map

yes

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can define user-defined aggregate functions for map-reduce-style calculations

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

one or two-phase-commit; repeatable reads; read commited

yes

ACID

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Role-based access control

Fine grained access control via users, groups and roles

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

F ree Tier and Enterprise Edition
» more

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