DBMS > KairosDB vs. SAP HANA vs. ScyllaDB vs. Splice Machine

System Properties Comparison KairosDB vs. SAP HANA vs. ScyllaDB vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

In-memory, column based data store. Available as appliance or cloud service

Cassandra and DynamoDB compatible wide column store

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Key-value store

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

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	4.15
Rank	#69	Overall
	#5	Wide column stores

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

github.com/kairosdb/kairosdb

www.sap.com/products/hana.html

www.scylladb.com

splicemachine.com

Technical documentation

kairosdb.github.io

help.sap.com/hana

docs.scylladb.com

splicemachine.com/how-it-works

Developer

SAP

ScyllaDB

Splice Machine

Initial release

2013

2010

2015

2014

Current release

1.2.2, November 2018

2.0 SPS07 (April 4, 2023), April 2023

ScyllaDB Open Source 6.0.2, July 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Open Source (AGPL), commercial license available

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Windows

Appliance or cloud-service

Linux

Linux
OS X
Solaris
Windows

Data scheme

schema-free

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.

Secondary indexes

yes

cluster global secondary indices

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL)

yes

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

SQLScript, R

yes, Lua

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

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 tables

yes

User concepts

Access control

simple password-based access control

yes

Access rights for users can be defined per object

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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