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DBMS > Apache Impala vs. KairosDB vs. SurrealDB vs. Vertica

System Properties Comparison Apache Impala vs. KairosDB vs. SurrealDB vs. Vertica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKairosDB  Xexclude from comparisonSurrealDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDistributed Time Series DBMS based on Cassandra or H2A fully ACID transactional, developer-friendly, multi-model DBMSCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSTime Series DBMSDocument store
Graph DBMS
Relational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.67
Rank#233  Overall
#20  Time Series DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteimpala.apache.orggithub.com/­kairosdb/­kairosdbsurrealdb.comwww.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmlkairosdb.github.iosurrealdb.com/­docsvertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSurrealDB LtdOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201320222005
Current release4.1.0, June 20221.2.2, November 2018v1.5.0, May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaRustC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
macOS
Windows
Linux
Data schemeyesschema-freeschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query languageFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Graphite protocol
HTTP REST
Telnet API
GraphQL
RESTful HTTP API
WebSocket
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBCJava
JavaScript infoNode.js
PHP
Python
Deno
Go
JavaScript (Node.js)
Rust
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrahorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandraMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberossimple password-based access controlyes, based on authentication and database rulesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaKairosDBSurrealDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
Apache ImpalaKairosDBSurrealDBVertica infoOpenText™ Vertica™
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