DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. eXtremeDB vs. LeanXcale vs. RavenDB vs. SAP HANA

System Properties Comparison Apache Impala vs. eXtremeDB vs. LeanXcale vs. RavenDB vs. SAP HANA

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisoneXtremeDB  Xexclude from comparisonLeanXcale  Xexclude from comparisonRavenDB  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNatively in-memory DBMS with options for persistency, high-availability and clusteringA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseIn-memory, column based data store. Available as appliance or cloud service
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Document storeRelational DBMS
Secondary database modelsDocument storeGraph DBMS
Spatial DBMS
Time Series DBMS
Document store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score44.69
Rank#22  Overall
#16  Relational DBMS
Websiteimpala.apache.orgwww.mcobject.comwww.leanxcale.comravendb.netwww.sap.com/­products/­hana.html
Technical documentationimpala.apache.org/­impala-docs.htmlwww.mcobject.com/­docs/­extremedb.htmravendb.net/­docshelp.sap.com/­hana
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMcObjectLeanXcaleHibernating RhinosSAP
Initial release20132001201520102010
Current release4.1.0, June 20228.2, 20215.4, July 20222.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoAGPL version 3, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono infoalso available as a cloud based service
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++C#
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Appliance or cloud-service
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono infosupport of XML interfaces availableno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith the option: eXtremeSQLyes infothrough Apache DerbySQL-like query language (RQL)yes
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
Lua
Python
Scala
C
Java
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesSQLScript, R
Triggersnoyes infoby defining eventsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning / shardingShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAuthorization levels configured per client per databaseyes
More information provided by the system vendor
Apache ImpalaeXtremeDBLeanXcaleRavenDBSAP HANA
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaeXtremeDBLeanXcaleRavenDBSAP HANA
Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

provided by Google News

McObject Announces the Release of eXtremeDB/rt 1.2
23 May 2023, Embedded Computing Design

Latest embedded DBMS supports asymmetric multiprocessing systems
24 May 2023, Embedded

McObject and Lynx Software Technologies Team Up for the First COTS Hard Real-Time DBMS for Mission- and Safety ...
21 October 2021, GlobeNewswire

The Data in Hard Real-time SCADA Systems Lets Companies Do More with Less
11 August 2023, Automation.com

McObject’s new eXtremeDB Cluster provides distributed database solution for real-time apps
20 July 2011, Embedded

provided by Google News

Combining operational and analytical databases in a single platform
26 May 2017, Cordis News

provided by Google News

RavenDB Launches Version 6.0 Lightning Fast Queries, Data Integrations, Corax Indexing Engine, and Sharding
3 October 2023, PR Newswire

RavenDB Welcomes David Baruc as Chief Revenue Officer: Seasoned Tech Leader to Drive Global Sales and ...
13 June 2023, PR Newswire

Install the NoSQL RavenDB Data System
14 May 2021, The New Stack

How I Created a RavenDB Python Client
23 September 2016, Visual Studio Magazine

RavenDB Adds Graph Queries
15 May 2019, Datanami

provided by Google News

Combine the Power of AI with Business Context Using SAP HANA Cloud Vector Engine
2 April 2024, SAP News

Automating the update process of a clustered SAP HANA DB using nZDT and Ansible | Amazon Web Services
16 November 2023, AWS Blog

SAP HANA Cloud Vector Engine
18 April 2024, IgniteSAP

Modernize consolidation in an SAP S/4 HANA environment | CCH Tagetik
9 April 2024, Wolters Kluwer

What are the options as SAP HANA 1.0 support in the Neo environment sunsets?
3 November 2023, ComputerWeekly.com

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here