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DBMS > Axibase vs. Datomic vs. etcd vs. Vertica

System Properties Comparison Axibase vs. Datomic vs. etcd vs. Vertica

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Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonDatomic  Xexclude from comparisonetcd  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA distributed reliable key-value storeCloud 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 modelTime Series DBMSRelational DBMSKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financewww.datomic.cometcd.io
github.com/­etcd-io/­etcd
www.vertica.com
Technical documentationdocs.datomic.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
vertica.com/­documentation
DeveloperAxibase CorporationCognitectOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320122005
Current release155851.0.7075, December 20233.4, August 201912.0.3, January 2023
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial infolimited edition freeOpen Source infoApache Version 2.0commercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ClojureGoC++
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
Windows infoexperimental
Linux
Data schemeyesyesschema-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 dateyes infoshort, integer, long, float, double, decimal, stringyesnoyes
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.nononono
Secondary indexesnoyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languagenonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
RESTful HTTP APIgRPC
JSON over HTTP
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
PHP
Python
R
Ruby
Clojure
Java
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesBy using transaction functionsyes, watching key changesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peershorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-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 methodsyesnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AxibaseDatomicetcdVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
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...
» more
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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AxibaseDatomicetcdVertica infoOpenText™ Vertica™
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