DBMS > Datastax Enterprise vs. etcd vs. H2 vs. SAP HANA vs. TimescaleDB

System Properties Comparison Datastax Enterprise vs. etcd vs. H2 vs. SAP HANA vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

A distributed reliable key-value store

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.datastax.com/products/datastax-enterprise

etcd.io
github.com/etcd-io/etcd

www.h2database.com

www.sap.com/products/hana.html

www.timescale.com

Technical documentation

docs.datastax.com

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.h2database.com/html/main.html

help.sap.com/hana

docs.timescale.com

Developer

DataStax

Thomas Mueller

SAP

Timescale

Initial release

2011

2005

2010

2017

Current release

6.8, April 2020

3.4, August 2019

2.2.220, July 2023

2.0 SPS07 (April 4, 2023), April 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

Server operating systems

Linux
OS X

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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 (CQL); Spark SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

gRPC
JSON over HTTP

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

SQLScript, R

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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 can be defined per object

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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